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src/data/roadmaps/mlops/content/terraform@dA9AE-3lTB6lN-X-_Byd2.md create mode 100644 src/data/roadmaps/mlops/content/tflite@YFo3NnwVst5EBTtLR-cJ1.md create mode 100644 src/data/roadmaps/mlops/content/version-control-systems@_NPGsGEjcLekjGisdDFWt.md create mode 100644 src/data/roadmaps/mlops/content/what-is-mlops@IghGpwAFVB067uOosmoDC.md diff --git a/src/data/roadmaps/mlops/content/airflow@AjZHJcxUY29WZbCvr3zrs.md b/src/data/roadmaps/mlops/content/airflow@AjZHJcxUY29WZbCvr3zrs.md new file mode 100644 index 000000000..06a61a4fa --- /dev/null +++ b/src/data/roadmaps/mlops/content/airflow@AjZHJcxUY29WZbCvr3zrs.md @@ -0,0 +1,13 @@ +# Airflow + +Airflow is a platform used to programmatically author, schedule, and monitor workflows. It allows you to define workflows as Directed Acyclic Graphs (DAGs) of tasks, where each task represents a unit of work. Airflow then executes these tasks in the specified order, handling dependencies, retries, and logging along the way. + +Visit the following resources to learn more: + +- [@official@Airflow](https://airflow.apache.org/) +- [@official@Airflow Docs](https://airflow.apache.org/docs) +- [@opensource@airflow](https://github.com/apache/airflow) +- [@article@What is Apache Airflow? For beginners](https://www.youtube.com/watch?v=CGxxVj13sOs) +- [@article@Building Pipelines In Apache Airflow – For Beginners](https://towardsdatascience.com/building-pipelines-in-apache-airflow-for-beginners-58f87a1512d5/) +- [@video@Apache Airflow Tutorial for Data Engineers](https://www.youtube.com/watch?v=y5rYZLBZ_Fw) +- [@feed@Explore top posts about Apache Airflow](https://app.daily.dev/tags/apache-airflow?ref=roadmapsh) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/ansible@-_obgPIUaZ4BVpg29xG_9.md b/src/data/roadmaps/mlops/content/ansible@-_obgPIUaZ4BVpg29xG_9.md new file mode 100644 index 000000000..e1ae7f43d --- /dev/null +++ b/src/data/roadmaps/mlops/content/ansible@-_obgPIUaZ4BVpg29xG_9.md @@ -0,0 +1,11 @@ +# Ansible + +Ansible is an open-source automation tool used to configure systems, deploy software, and orchestrate more advanced IT tasks. It uses a simple, human-readable language (YAML) to define automation tasks, called playbooks. Ansible works by connecting to nodes (servers, virtual machines, etc.) and pushing out small programs called "Ansible modules" to them. These modules are then executed on the nodes, and the modules are removed when finished. + +Visit the following resources to learn more: + +- [@official@Ansible Website](https://www.ansible.com/) +- [@article@What is Ansible? A Tool to Automate Parts of Your Job](https://www.freecodecamp.org/news/what-is-ansible/) +- [@video@Ansible in 100 Seconds](https://www.youtube.com/watch?v=xRMPKQweySE) +- [@video@Ansible Full Course for Beginners](https://www.youtube.com/watch?v=9Ua2b06oAr4) +- [@video@Ansible Full Course to Zero to Hero](https://www.youtube.com/watch?v=GROqwFFLl3s) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/cicd@oUhlUoWQQ1txx_sepD5ev.md b/src/data/roadmaps/mlops/content/cicd@oUhlUoWQQ1txx_sepD5ev.md new file mode 100644 index 000000000..36f821925 --- /dev/null +++ b/src/data/roadmaps/mlops/content/cicd@oUhlUoWQQ1txx_sepD5ev.md @@ -0,0 +1,11 @@ +# CI/CD + +CI/CD, which stands for Continuous Integration and Continuous Delivery/Deployment, is a software development practice focused on automating and streamlining the process of building, testing, and releasing software changes. Continuous Integration involves frequently merging code changes into a central repository, followed by automated builds and tests. Continuous Delivery/Deployment then automates the release of these changes to various environments, ultimately aiming for faster and more reliable software releases. + +Visit the following resources to learn more: + +- [@official@What is CI/CD?](https://about.gitlab.com/topics/ci-cd/) +- [@article@A Primer: Continuous Integration and Continuous Delivery (CI/CD)](https://thenewstack.io/a-primer-continuous-integration-and-continuous-delivery-ci-cd/) +- [@feed@Articles about CI/CD](https://app.daily.dev/tags/version-control?ref=roadmapsh) +- [@article@DevOps CI/CD Explained in 100 Seconds](https://thenewstack.io/category/ci-cd/) +- [@video@Automate your Workflows with GitHub Actions](https://www.youtube.com/watch?v=scEDHsr3APg) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/cloud-native-ml-services@kbfucfIO5KCsuv3jKbHTa.md b/src/data/roadmaps/mlops/content/cloud-native-ml-services@kbfucfIO5KCsuv3jKbHTa.md index 6ab288d77..8fdbbd3da 100644 --- a/src/data/roadmaps/mlops/content/cloud-native-ml-services@kbfucfIO5KCsuv3jKbHTa.md +++ b/src/data/roadmaps/mlops/content/cloud-native-ml-services@kbfucfIO5KCsuv3jKbHTa.md @@ -6,4 +6,6 @@ Visit the following resources to learn more: - [@official@AWS Sage Maker](https://aws.amazon.com/sagemaker/) - [@official@Azure ML](https://azure.microsoft.com/en-gb/products/machine-learning) +- [@official@Vertex AI Platform](https://cloud.google.com/vertex-ai?hl=en) +- [@article@What is cloud native?](https://cloud.google.com/learn/what-is-cloud-native?hl=en) - [@video@What is Cloud Native?](https://www.youtube.com/watch?v=fp9_ubiKqFU) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/cml@MLob7b468ZgNX7-cURqmJ.md b/src/data/roadmaps/mlops/content/cml@MLob7b468ZgNX7-cURqmJ.md new file mode 100644 index 000000000..c4c48e58a --- /dev/null +++ b/src/data/roadmaps/mlops/content/cml@MLob7b468ZgNX7-cURqmJ.md @@ -0,0 +1,9 @@ +# Continuous Machine Learning (CML) + +Continuous Machine Learning (CML) is a tool designed to bring continuous integration and continuous delivery (CI/CD) principles to machine learning projects. It allows data scientists and machine learning engineers to automate the process of training, evaluating, and deploying machine learning models. CML integrates with existing CI/CD systems to provide feedback on model performance and data quality with each code change. + +Visit the following resources to learn more: + +- [@article@CML](https://cml.dev/) +- [@article@Get Started with CML](https://cml.dev/doc/start) +- [@article@Continuous Machine Learning](https://towardsdatascience.com/continuous-machine-learning-e1ffb847b8da/) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/data-engineering-fundamentals@VykbCu7LWIx8fQpqKzoA7.md b/src/data/roadmaps/mlops/content/data-engineering-fundamentals@VykbCu7LWIx8fQpqKzoA7.md index 322673dad..faed8db16 100644 --- a/src/data/roadmaps/mlops/content/data-engineering-fundamentals@VykbCu7LWIx8fQpqKzoA7.md +++ b/src/data/roadmaps/mlops/content/data-engineering-fundamentals@VykbCu7LWIx8fQpqKzoA7.md @@ -6,4 +6,5 @@ Visit the following resources to learn more: - [@roadmap@Visit the Dedicated Data Engineer Roadmap](https://roadmap.sh/data-engineer) - [@article@Data Engineering 101](https://www.redpanda.com/guides/fundamentals-of-data-engineering) +- [@article@How to Become a Data Engineer](https://towardsdatascience.com/how-to-become-a-data-engineer-c0319cb226c2/) - [@video@Fundamentals of Data Engineering](https://www.youtube.com/watch?v=mPSzL8Lurs0) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/data-lakes--warehouses@wOogVDV4FIDLXVPwFqJ8C.md b/src/data/roadmaps/mlops/content/data-lakes--warehouses@wOogVDV4FIDLXVPwFqJ8C.md index 88104a4b3..4c588487b 100644 --- a/src/data/roadmaps/mlops/content/data-lakes--warehouses@wOogVDV4FIDLXVPwFqJ8C.md +++ b/src/data/roadmaps/mlops/content/data-lakes--warehouses@wOogVDV4FIDLXVPwFqJ8C.md @@ -5,5 +5,7 @@ Data lakes and data warehouses are both systems for storing large amounts of dat Visit the following resources to learn more: - [@article@Data Lake Definition](https://azure.microsoft.com/en-gb/resources/cloud-computing-dictionary/what-is-a-data-lake) +- [@article@Data Lake VS Data Warehouse](https://towardsdatascience.com/data-lake-vs-data-warehouse-2e3df551b800/) - [@video@What is a Data Lake?](https://www.youtube.com/watch?v=LxcH6z8TFpI) -- [@video@What is a Data Warehouse?](https://www.youtube.com/watch?v=k4tK2ttdSDg) \ No newline at end of file +- [@video@What is a Data Warehouse?](https://www.youtube.com/watch?v=k4tK2ttdSDg) +- [@video@Data Lake VS Data Warehouse VS Data Marts](https://www.youtube.com/watch?v=w9-WoReNKHk) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/data-lineage@6XgP_2NLuiw654zvTyueT.md b/src/data/roadmaps/mlops/content/data-lineage@6XgP_2NLuiw654zvTyueT.md new file mode 100644 index 000000000..3091b8dac --- /dev/null +++ b/src/data/roadmaps/mlops/content/data-lineage@6XgP_2NLuiw654zvTyueT.md @@ -0,0 +1,10 @@ +# Data Lineage and Feature Stores + +**Data Lineage** refers to the life-cycle of data, including its origins, movements, characteristics and quality. It's a critical component in MLOps for tracking the journey of data through every process in a pipeline, from raw input to model output. Data lineage helps in maintaining transparency, ensuring compliance, and facilitating data debugging or tracing data-related bugs. It provides a clear representation of data sources, transformations, and dependencies, thereby aiding in audits, governance, or reproduction of machine learning models. + +Visit the following resources to learn more: + +- [@article@What is Data Lineage?](https://www.ibm.com/topics/data-lineage) +- [@article@What is a Feature Store](https://www.snowflake.com/guides/what-feature-store-machine-learning/) +- [@article@The Ultimate Guide To Data Lineage](https://www.montecarlodata.com/blog-data-lineage/) +- [@video@What is Data Lineage?](https://www.youtube.com/watch?v=Jar5Rr_7TOU) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/data-pipelines@cOg3ejZRYE-u-M0c89IjM.md b/src/data/roadmaps/mlops/content/data-pipelines@cOg3ejZRYE-u-M0c89IjM.md index 0dccf0794..2f44e3878 100644 --- a/src/data/roadmaps/mlops/content/data-pipelines@cOg3ejZRYE-u-M0c89IjM.md +++ b/src/data/roadmaps/mlops/content/data-pipelines@cOg3ejZRYE-u-M0c89IjM.md @@ -5,4 +5,6 @@ Data pipelines are a series of automated processes that transport and transform Visit the following resources to learn more: - [@article@What is a Data Pipeline? - IBM](https://www.ibm.com/topics/data-pipeline) +- [@article@How to Build Data Pipelines for Machine Learning](https://towardsdatascience.com/how-to-build-data-pipelines-for-machine-learning-b97bbef050a5/) +- [@article@Read Articles about Data Pipelines](https://towardsdatascience.com/tag/data-pipeline/) - [@video@What are Data Pipelines?](https://www.youtube.com/watch?v=oKixNpz6jNo) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/deep-learning@1kk8KDWH-LrPt8SjkpTcX.md b/src/data/roadmaps/mlops/content/deep-learning@1kk8KDWH-LrPt8SjkpTcX.md new file mode 100644 index 000000000..863576566 --- /dev/null +++ b/src/data/roadmaps/mlops/content/deep-learning@1kk8KDWH-LrPt8SjkpTcX.md @@ -0,0 +1,11 @@ +# Deep Learning + +Deep learning is a subset of machine learning that uses artificial neural networks with multiple layers (hence "deep") to analyze data with complex structures. These networks learn hierarchical representations of data, where each layer extracts increasingly abstract features from the previous layer. This allows deep learning models to automatically discover intricate patterns and relationships in data, making them particularly effective for tasks like image recognition, natural language processing, and speech recognition. + +Visit the following resources to learn more: + +- [@roadmap@Visit the Dedicated Machine Learning Roadmap](https://roadmap.sh/machine-learning) +- [@book@Deep Learning Book](https://www.deeplearningbook.org/) +- [@course@Practical Deep Learning](https://course.fast.ai/) +- [@article@Introduction to Deep Learning](https://www.ibm.com/topics/deep-learning) +- [@video@What is a Neural Network?](https://www.youtube.com/watch?v=aircAruvnKk) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/dvc@qLKM1zGUhuyBwh_uXSyJJ.md b/src/data/roadmaps/mlops/content/dvc@qLKM1zGUhuyBwh_uXSyJJ.md new file mode 100644 index 000000000..0028185fd --- /dev/null +++ b/src/data/roadmaps/mlops/content/dvc@qLKM1zGUhuyBwh_uXSyJJ.md @@ -0,0 +1,11 @@ +# DVC + +DVC (Data Version Control) is an open-source tool designed to bring version control principles to machine learning projects, specifically for data and models. It extends Git's capabilities to handle large files, datasets, and machine learning models, which are typically not well-suited for traditional version control systems. DVC tracks changes to data and models, allowing you to reproduce experiments, revert to previous versions, and collaborate effectively on data-driven projects. + +Visit the following resources to learn more: + +- [@official@DVC](https://dvc.org/) +- [@official@Get Started with DVC](https://doc.dvc.org/start) +- [@article@The Complete Guide to Data Version Control With DVC](https://www.datacamp.com/tutorial/data-version-control-dvc) +- [@article@Data and Machine Learning Model Versioning with DVC](https://towardsdatascience.com/data-and-machine-learning-model-versioning-with-dvc-34fdadd06b15/) +- [@video@Versioning Data with DVC (Hands-On Tutorial!)](https://www.youtube.com/watch?v=kLKBcPonMYw) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/edge-ai@w8z91Hlqm0sPligYD3VCk.md b/src/data/roadmaps/mlops/content/edge-ai@w8z91Hlqm0sPligYD3VCk.md new file mode 100644 index 000000000..196a9de0c --- /dev/null +++ b/src/data/roadmaps/mlops/content/edge-ai@w8z91Hlqm0sPligYD3VCk.md @@ -0,0 +1,11 @@ +# Edge AI + +Edge AI refers to running machine learning models directly on devices, like smartphones, sensors, or embedded systems, rather than relying on a central server or cloud infrastructure. This approach brings computation and data processing closer to the source of data generation. This enables faster response times, reduced latency, enhanced privacy, and the ability to operate in environments with limited or no network connectivity. + +Visit the following resources to learn more: + +- [@article@What Is Edge AI and How Does It Work?](https://blogs.nvidia.com/blog/what-is-edge-ai/) +- [@article@What is Edge AI?](https://www.ibm.com/think/topics/edge-ai) +- [@article@What is Edge Computing - Cloudflare Docs](https://www.cloudflare.com/learning/serverless/glossary/what-is-edge-computing/) +- [@article@What is Edge Computing? Is It More Than a Buzzword?](https://www.howtogeek.com/devops/what-is-edge-computing-is-it-more-than-a-buzzword/) +- [@course@What Is Edge Computing?](https://www.udemy.com/course/edge-computing/) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/experiment-tracking@fGGWKmAJ50Ke6wWJBEgby.md b/src/data/roadmaps/mlops/content/experiment-tracking@fGGWKmAJ50Ke6wWJBEgby.md new file mode 100644 index 000000000..66bc2793f --- /dev/null +++ b/src/data/roadmaps/mlops/content/experiment-tracking@fGGWKmAJ50Ke6wWJBEgby.md @@ -0,0 +1,10 @@ +# Experiment Tracking and Model Registry + +**Experiment Tracking** is an essential part of MLOps, providing a system to monitor and record the different experiments conducted during the machine learning model development process. This involves capturing, organizing and visualizing the metadata associated with each experiment, such as hyperparameters used, models produced, metrics like accuracy or loss, and other information about the computational environment. This tracking allows for reproducibility of experiments, comparison across different experiment runs, and helps in identifying the best models. + +Visit the following resources to learn more: + +- [@article@Experiment Tracking](https://madewithml.com/courses/mlops/experiment-tracking/#dashboard) +- [@article@ML Flow Model Registry](https://mlflow.org/docs/latest/model-registry.html) +- [@article@What is a Model Registry?](https://jfrog.com/learn/mlops/model-registry/) +- [@video@Introduction to Experiment Tracking](https://www.youtube.com/watch?v=hctZDeB14-s) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/explainable-ai@qy37ppIWDT_we-duuHwgT.md b/src/data/roadmaps/mlops/content/explainable-ai@qy37ppIWDT_we-duuHwgT.md new file mode 100644 index 000000000..61c8fcfb7 --- /dev/null +++ b/src/data/roadmaps/mlops/content/explainable-ai@qy37ppIWDT_we-duuHwgT.md @@ -0,0 +1,9 @@ +# Explainable AI + +Explainable AI (XAI) refers to methods and techniques used to make the decisions of machine learning models understandable to humans. It aims to shed light on how a model arrives at a particular prediction, identifying the factors that influenced the outcome. This allows users to understand, trust, and effectively manage AI systems. + +Visit the following resources to learn more: + +- [@article@What is Explainable AI (XAI)?](https://www.ibm.com/think/topics/explainable-ai) +- [@article@Explainable AI (XAI) | Giskard](https://www.giskard.ai/glossary/explainable-ai-xai) +- [@video@Explainable AI: Demystifying AI Agents Decision-Making](https://www.youtube.com/watch?v=yJkCuEu3K68) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/flink@o6GQ3-8DgDtHzdX6yeg1w.md b/src/data/roadmaps/mlops/content/flink@o6GQ3-8DgDtHzdX6yeg1w.md index 556ec555b..f97d24836 100644 --- a/src/data/roadmaps/mlops/content/flink@o6GQ3-8DgDtHzdX6yeg1w.md +++ b/src/data/roadmaps/mlops/content/flink@o6GQ3-8DgDtHzdX6yeg1w.md @@ -6,4 +6,6 @@ Visit the following resources to learn more: - [@official@Apache Flink Documentation](https://flink.apache.org/) - [@article@Apache Flink](https://www.tutorialspoint.com/apache_flink/apache_flink_introduction.htm) +- [@article@An Introduction to Stream Processing with Apache Flink](https://towardsdatascience.com/an-introduction-to-stream-processing-with-apache-flink-b4acfa58f14d/) +- [@video@Introduction | Apache Flink 101](https://www.youtube.com/watch?v=3cg5dABA6mo&list=PLa7VYi0yPIH1UdmQcnUr8lvjbUV8JriK0) - [@feed@Explore top posts about Apache Flink](https://app.daily.dev/tags/apache-flink?ref=roadmapsh) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/github-actions@SCn-6w1UEQwoLQ_dOPpL5.md b/src/data/roadmaps/mlops/content/github-actions@SCn-6w1UEQwoLQ_dOPpL5.md new file mode 100644 index 000000000..c657321f6 --- /dev/null +++ b/src/data/roadmaps/mlops/content/github-actions@SCn-6w1UEQwoLQ_dOPpL5.md @@ -0,0 +1,10 @@ +# GitHub Actions + +GitHub Actions is a continuous integration and continuous delivery (CI/CD) platform that allows you to automate your software development workflows directly in your GitHub repository. You can use it to build, test, and deploy your code, as well as automate other tasks like managing issues and pull requests. Workflows are defined in YAML files and triggered by events in your repository, such as pushes, pull requests, or scheduled times. + +Visit the following resources to learn more: + +- [@official@GitHub Actions Documentation](https://docs.github.com/en/actions) +- [@article@GitHub Actions Guide](https://octopus.com/devops/github-actions/?utm_source=roadmap&utm_medium=link&utm_campaign=devops-ci-cd-github-actions) +- [@video@What is GitHub Actions?](https://www.youtube.com/watch?v=URmeTqglS58) +- [@video@Automate your Workflow with GitHub Actions](https://www.youtube.com/watch?v=nyKZTKQS_EQ) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/gitlab@mu56TlVkhhgVzzESDRobc.md b/src/data/roadmaps/mlops/content/gitlab@mu56TlVkhhgVzzESDRobc.md new file mode 100644 index 000000000..80cc10fa3 --- /dev/null +++ b/src/data/roadmaps/mlops/content/gitlab@mu56TlVkhhgVzzESDRobc.md @@ -0,0 +1,10 @@ +# GitLab + +GitLab is a web-based DevOps platform that provides a single application for all stages of the software development lifecycle. It offers features like source code management (using Git), CI/CD pipelines, issue tracking, and project management. GitLab allows teams to collaborate on code, automate build, test, and deployment processes, and manage projects from planning to monitoring. + +Visit the following resources to learn more: + +- [@official@GitLab Website](https://gitlab.com/) +- [@official@GitLab Docs](https://docs.gitlab.com/) +- [@article@Read articles about Gitlab](https://towardsdatascience.com/tag/gitlab/) +- [@video@GitLab Explained: What is GitLab and Why Use It?](https://www.youtube.com/watch?v=bnF7f1zGpo4) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/graphana@YmRN43yAFF97c7MgNaiqs.md b/src/data/roadmaps/mlops/content/graphana@YmRN43yAFF97c7MgNaiqs.md new file mode 100644 index 000000000..5e93e7e66 --- /dev/null +++ b/src/data/roadmaps/mlops/content/graphana@YmRN43yAFF97c7MgNaiqs.md @@ -0,0 +1,12 @@ +# Grafana + +Grafana is an open-source data visualization and monitoring tool. It allows users to query, visualize, alert on, and explore metrics, logs, and traces. Grafana connects to various data sources, such as Prometheus, Graphite, Elasticsearch, and InfluxDB, to create customizable dashboards that display real-time data and historical trends. + +Visit the following resources to learn more: + +- [@official@Grafana](https://grafana.com/) +- [@official@Grafana Docs](https://grafana.com/docs/) +- [@official@Grafana Webinars and Videos](https://grafana.com/videos/) +- [@article@What is Grafana?](https://www.redhat.com/en/topics/data-services/what-is-grafana) +- [@video@Grafana Explained in Under 5 Minutes ⏲](https://www.youtube.com/watch?v=lILY8eSspEo) +- [@video@Grafana for Beginners Ep. 1](https://www.youtube.com/watch?v=TQur9GJHIIQ&list=PLDGkOdUX1Ujo27m6qiTPPCpFHVfyKq9jT) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/infrastructure-as-code@sf67bSL7HAx6iN7S6MYKs.md b/src/data/roadmaps/mlops/content/infrastructure-as-code@sf67bSL7HAx6iN7S6MYKs.md index 5a1dfb250..1ac7eedfd 100644 --- a/src/data/roadmaps/mlops/content/infrastructure-as-code@sf67bSL7HAx6iN7S6MYKs.md +++ b/src/data/roadmaps/mlops/content/infrastructure-as-code@sf67bSL7HAx6iN7S6MYKs.md @@ -4,7 +4,6 @@ Infrastructure as Code (IaC) is a modern approach to managing and provisioning I Visit the following resources to learn more: -- [@roadmap@Visit Dedicated Terraform Roadmap](https://roadmap.sh/terraform) - [@article@What is Infrastructure as Code?](https://www.redhat.com/en/topics/automation/what-is-infrastructure-as-code-iac) - [@video@Terraform Course for Beginners](https://www.youtube.com/watch?v=SLB_c_ayRMo) - [@video@8 Terraform Best Practices](https://www.youtube.com/watch?v=gxPykhPxRW0) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/jenkins@75mlW2JoUqSNFK2IDfqFP.md b/src/data/roadmaps/mlops/content/jenkins@75mlW2JoUqSNFK2IDfqFP.md new file mode 100644 index 000000000..75fda5727 --- /dev/null +++ b/src/data/roadmaps/mlops/content/jenkins@75mlW2JoUqSNFK2IDfqFP.md @@ -0,0 +1,10 @@ +# Jenkins + +Jenkins is an open-source automation server that helps automate the software development processes, including building, testing, and deploying code. It provides a platform for continuous integration and continuous delivery (CI/CD), allowing teams to automate repetitive tasks and streamline their workflows. Jenkins uses plugins to support various tools and technologies, making it highly customizable and adaptable to different project requirements. + +Visit the following resources to learn more: + +- [@official@Jenkins Website](https://www.jenkins.io/) +- [@official@Jenkins Getting Started Guide](https://www.jenkins.io/doc/pipeline/tour/getting-started/) +- [@article@Jenkins Tutorial](https://octopus.com/devops/jenkins/jenkins-tutorial/?utm_source=roadmap&utm_medium=link&utm_campaign=devops-ci-cd-gitlab-ci) +- [@video@Learn Jenkins! Complete Jenkins Course - Zero to Hero](https://www.youtube.com/watch?v=6YZvp2GwT0A) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/jetson@Wpv_zRshtTFXNqp1S7m0F.md b/src/data/roadmaps/mlops/content/jetson@Wpv_zRshtTFXNqp1S7m0F.md new file mode 100644 index 000000000..7813194a2 --- /dev/null +++ b/src/data/roadmaps/mlops/content/jetson@Wpv_zRshtTFXNqp1S7m0F.md @@ -0,0 +1,9 @@ +# Jetson + +NVIDIA Jetson is a series of embedded computing systems designed for AI and robotics applications. These systems-on-modules (SoMs) provide high-performance processing capabilities in a compact, energy-efficient form factor, enabling developers to deploy AI models and perform complex computations directly on edge devices. Jetson platforms are commonly used in applications like autonomous vehicles, drones, smart cameras, and industrial automation, where real-time data processing and low latency are critical. + +Visit the following resources to learn more: + +- [@official@NVIDIA Jetson Modules](https://developer.nvidia.com/embedded/jetson-modules) +- [@article@What Is NVIDIA Jetson? A Beginner’s Guide to Powerful Edge AI Modules](https://blog.aetherix.com/nvidia-jetson-beginners-guide/) +- [@video@NVIDIA Jetson Orin Nano Super COMPLETE Setup Guide & Tutorial](https://www.youtube.com/watch?v=-PjMC0gyH9s) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/kafka@fMNwzhgLgHlAZJ9NvKikR.md b/src/data/roadmaps/mlops/content/kafka@fMNwzhgLgHlAZJ9NvKikR.md index 61e17d8ec..71b9d068c 100644 --- a/src/data/roadmaps/mlops/content/kafka@fMNwzhgLgHlAZJ9NvKikR.md +++ b/src/data/roadmaps/mlops/content/kafka@fMNwzhgLgHlAZJ9NvKikR.md @@ -5,5 +5,6 @@ Kafka is a distributed, fault-tolerant, high-throughput streaming platform. It's Visit the following resources to learn more: - [@official@Apache Kafka Quickstart](https://kafka.apache.org/quickstart) +- [@article@Read Articles about Kafka](https://towardsdatascience.com/tag/apache-kafka/) - [@video@Apache Kafka Fundamentals](https://www.youtube.com/watch?v=B5j3uNBH8X4) - [@feed@Explore top posts about Kafka](https://app.daily.dev/tags/kafka?ref=roadmapsh) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/kubeflow@QEayqA8zYsJn0rQYz-4zv.md b/src/data/roadmaps/mlops/content/kubeflow@QEayqA8zYsJn0rQYz-4zv.md new file mode 100644 index 000000000..5e6ba08d1 --- /dev/null +++ b/src/data/roadmaps/mlops/content/kubeflow@QEayqA8zYsJn0rQYz-4zv.md @@ -0,0 +1,11 @@ +# Kubeflow + +Kubeflow is an open-source machine learning platform designed to simplify the deployment and management of ML workflows on Kubernetes. It provides tools and components for building, training, and deploying machine learning models, allowing users to create portable and scalable ML pipelines. Kubeflow aims to make it easier for data scientists and engineers to leverage Kubernetes for their machine learning projects, handling tasks like resource management, model serving, and pipeline orchestration. + +Visit the following resources to learn more: + +- [@official@Kubeflow](https://www.kubeflow.org/) +- [@opensource@kubeflow](https://github.com/kubeflow/kubeflow) +- [@article@What is Kubeflow?](https://cloud.google.com/discover/what-is-kubeflow?hl=en) +- [@video@Kubeflow Explained for Beginners](https://www.youtube.com/watch?v=hvzEPlRdJ2Q) +- [@video@Intro to Kubeflow Pipelines](https://www.youtube.com/watch?v=_AY8mmbR1o4&list=PLIivdWyY5sqLS4lN75RPDEyBgTro_YX7x) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/kubernetes@XQoK9l-xtN2J8ZV8dw53X.md b/src/data/roadmaps/mlops/content/kubernetes@XQoK9l-xtN2J8ZV8dw53X.md index d80146164..77285a4da 100644 --- a/src/data/roadmaps/mlops/content/kubernetes@XQoK9l-xtN2J8ZV8dw53X.md +++ b/src/data/roadmaps/mlops/content/kubernetes@XQoK9l-xtN2J8ZV8dw53X.md @@ -1,6 +1,6 @@ # Kubernetes -Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. By orchestrating containers across multiple machines, Kubernetes ensures high availability and efficient resource utilization, making it a powerful tool for managing complex deployments. +Kubernetes is an open-source system for automating the deployment, scaling, and management of containerized applications. It groups containers that make up an application into logical units for easy management and discovery. By orchestrating containers across multiple machines, Kubernetes ensures high availability and efficient resource utilization, making it a powerful tool for managing complex deployments. Visit the following resources to learn more: diff --git a/src/data/roadmaps/mlops/content/lime@pVSlVHXIap0unFxLGM-lQ.md b/src/data/roadmaps/mlops/content/lime@pVSlVHXIap0unFxLGM-lQ.md new file mode 100644 index 000000000..d98ad6e45 --- /dev/null +++ b/src/data/roadmaps/mlops/content/lime@pVSlVHXIap0unFxLGM-lQ.md @@ -0,0 +1,9 @@ +# LIME + +LIME (Local Interpretable Model-agnostic Explanations) is a technique used to understand the predictions of machine learning models. It works by approximating the model locally with a simpler, interpretable model, such as a linear model. This simpler model is trained on perturbations of the data point being explained, allowing users to understand which features are most important for that specific prediction. + +Visit the following resources to learn more: + +- [@opensource@lime](https://github.com/marcotcr/lime) +- [@article@Explainable AI - Understanding and Trusting Machine Learning Models](https://www.datacamp.com/tutorial/explainable-ai-understanding-and-trusting-machine-learning-models) +- [@video@Explainable AI explained! | #3 LIME](https://www.youtube.com/watch?v=d6j6bofhj2M) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/machine-learning@6uGYeXZn5fW2qPfSb8GJb.md b/src/data/roadmaps/mlops/content/machine-learning@6uGYeXZn5fW2qPfSb8GJb.md new file mode 100644 index 000000000..84d4e28ec --- /dev/null +++ b/src/data/roadmaps/mlops/content/machine-learning@6uGYeXZn5fW2qPfSb8GJb.md @@ -0,0 +1,9 @@ + + +Visit the following resources to learn more: + +- [@roadmap@Visit the Dedicated Machine Learning Roadmap](https://roadmap.sh/machine-learning) +- [@book@Machine Learning: The Basics](https://alexjungaalto.github.io/MLBasicsBook.pdf) +- [@article@What is Machine Learning (ML)?](https://www.ibm.com/topics/machine-learning) +- [@video@What is Machine Learning?](https://www.youtube.com/watch?v=9gGnTQTYNaE) +- [@video@Complete Machine Learning in One Video | Machine Learning Tutorial For Beginners 2025 | Simplilearn](https://www.youtube.com/watch?v=PtYRUoJRE9s) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/maths--statistics@C4KbkZ7c8TspXa3RBOCug.md b/src/data/roadmaps/mlops/content/maths--statistics@C4KbkZ7c8TspXa3RBOCug.md new file mode 100644 index 000000000..498d6c46c --- /dev/null +++ b/src/data/roadmaps/mlops/content/maths--statistics@C4KbkZ7c8TspXa3RBOCug.md @@ -0,0 +1,13 @@ +# Maths & Statistics + +Mathematics and statistics provide the foundational principles for understanding and building machine learning models. These disciplines offer the tools to analyze data, quantify uncertainty, and optimize model performance. Key areas include linear algebra for data representation and manipulation, calculus for optimization algorithms, probability theory for handling uncertainty, and statistical inference for drawing conclusions from data. + +Visit the following resources to learn more: + +- [@article@Computer Science 70, 001 - Spring 2015 - Discrete Mathematics and Probability Theory](http://www.infocobuild.com/education/audio-video-courses/computer-science/cs70-spring2015-berkeley.html) +- [@article@Discrete Mathematics By IIT Ropar NPTEL](https://nptel.ac.in/courses/106/106/106106183/) +- [@article@Introduction to Statistics](https://imp.i384100.net/3eRv4v) +- [@book@Introductory Statistics](https://assets.openstax.org/oscms-prodcms/media/documents/IntroductoryStatistics-OP_i6tAI7e.pdf) +- [@video@Lec 1 | MIT 6.042J Mathematics for Computer Science, Fall 2010](https://www.youtube.com/watch?v=L3LMbpZIKhQ&list=PLB7540DEDD482705B) +- [@video@Discrete Mathematics by Shai Simonson (19 videos)](https://www.youtube.com/playlist?list=PLWX710qNZo_sNlSWRMVIh6kfTjolNaZ8t) +- [@video@tatistics - A Full University Course on Data Science Basics](https://www.youtube.com/watch?v=xxpc-HPKN28) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/mlflow@93MPXEulKgPnuRlp7F-Nj.md b/src/data/roadmaps/mlops/content/mlflow@93MPXEulKgPnuRlp7F-Nj.md new file mode 100644 index 000000000..157aa4f8a --- /dev/null +++ b/src/data/roadmaps/mlops/content/mlflow@93MPXEulKgPnuRlp7F-Nj.md @@ -0,0 +1,13 @@ +# MLflow + +MLflow is an open-source platform designed to manage the complete machine learning lifecycle. It provides tools for tracking experiments, packaging code into reproducible runs, and deploying models to various platforms. MLflow helps data scientists and engineers streamline their workflows, collaborate effectively, and ensure the reliability of their machine learning projects. + +Visit the following resources to learn more: + +- [@official@MLFlow](https://mlflow.org/) +- [@official@MLFlow Docs](https://mlflow.org/docs/latest/) +- [@opensource@mlflow](https://github.com/mlflow/mlflow) +- [@article@Streamline Your Machine Learning Workflow with MLFlow](https://www.datacamp.com/tutorial/mlflow-streamline-machine-learning-workflow) +- [@article@Comprehensive Guide to MlFlow](https://towardsdatascience.com/comprehensive-guide-to-mlflow-b84086b002ae/) +- [@video@MLFlow Tutorial | ML Ops Tutorial](https://www.youtube.com/watch?v=6ngxBkx05Fs) +- [@video@MLflow for Machine Learning Development - Video Introduction](https://www.youtube.com/watch?v=5pPflDSdFLg&list=PLQqR_3C2fhUUOmaeowgv4WquvH515zVmo) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/model-evaluation@nS4igSghzVFwamhVOwCjm.md b/src/data/roadmaps/mlops/content/model-evaluation@nS4igSghzVFwamhVOwCjm.md new file mode 100644 index 000000000..d382f406b --- /dev/null +++ b/src/data/roadmaps/mlops/content/model-evaluation@nS4igSghzVFwamhVOwCjm.md @@ -0,0 +1,10 @@ +# Model Evaluation + +Model evaluation is the process of assessing the performance of a machine learning model using various metrics and techniques. It helps determine how well the model generalizes to unseen data and whether it meets the desired performance criteria. This involves using different evaluation metrics depending on the type of problem (e.g., accuracy, precision, recall, F1-score for classification; RMSE, MAE for regression) and employing techniques like cross-validation to obtain a reliable estimate of the model's performance. + +Visit the following resources to learn more: + +- [@article@What is Model Evaluation](https://domino.ai/data-science-dictionary/model-evaluation) +- [@article@Model Evaluation Metrics](https://www.markovml.com/blog/model-evaluation-metrics) +- [@article@Read Articles about Model Evaluation](https://towardsdatascience.com/tag/model-evaluation/) +- [@video@How to evaluate ML models | Evaluation metrics for machine learning](https://www.youtube.com/watch?v=LbX4X71-TFI) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/model-training--serving@zsW1NRb0dMgS-KzWsI0QU.md b/src/data/roadmaps/mlops/content/model-training--serving@zsW1NRb0dMgS-KzWsI0QU.md index a692d0b42..5a16bd55c 100644 --- a/src/data/roadmaps/mlops/content/model-training--serving@zsW1NRb0dMgS-KzWsI0QU.md +++ b/src/data/roadmaps/mlops/content/model-training--serving@zsW1NRb0dMgS-KzWsI0QU.md @@ -4,7 +4,7 @@ Model Training refers to the phase in the Machine Learning (ML) pipeline where w Visit the following resources to learn more: -- [@opensource@ML Deployment k8s Fast API](https://github.com/sayakpaul/ml-deployment-k8s-fastapi/) -- [@article@MLOps Principles](https://ml-ops.org/content/mlops-principles) -- [@article@ML deployment with k8s FastAPI, Building an ML app with FastAPI](https://dev.to/bravinsimiyu/beginner-guide-on-how-to-build-a-machine-learning-app-with-fastapi-part-ii-deploying-the-fastapi-application-to-kubernetes-4j6g) -- [@article@KServe Tutorial](https://towardsdatascience.com/kserve-highly-scalable-machine-learning-deployment-with-kubernetes-aa7af0b71202) \ No newline at end of file +- [@opensource@What is model training?](https://www.ibm.com/think/topics/model-training) +- [@article@What Is AI Model Training & Why Is It Important?](https://www.oracle.com/uk/artificial-intelligence/ai-model-training/) +- [@article@KServe Tutorial](https://towardsdatascience.com/kserve-highly-scalable-machine-learning-deployment-with-kubernetes-aa7af0b71202) +- [@video@Five Steps to Create a New AI Model](https://www.youtube.com/watch?v=jcgaNrC4ElU&t=172s) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/monitoring--observability@fR4Qr_ifoBLTpxdkJ50rB.md b/src/data/roadmaps/mlops/content/monitoring--observability@fR4Qr_ifoBLTpxdkJ50rB.md new file mode 100644 index 000000000..0eccb7808 --- /dev/null +++ b/src/data/roadmaps/mlops/content/monitoring--observability@fR4Qr_ifoBLTpxdkJ50rB.md @@ -0,0 +1,10 @@ +# Monitoring & Observability + +Monitoring and observability involve tracking the performance and health of machine learning models and the infrastructure they rely on. This includes gathering metrics, logs, and traces to understand how models are behaving in production, identify potential issues like performance degradation or data drift, and gain insights into the overall system's operation. The goal is to ensure models are accurate, reliable, and deliver value as expected. + +Visit the following resources to learn more: + +- [@article@What’s the Difference Between Observability and Monitoring?](https://aws.amazon.com/compare/the-difference-between-monitoring-and-observability/) +- [@article@Observability and Instrumentation: What They Are and Why They Matter](https://newrelic.com/blog/best-practices/observability-instrumentation) +- [@video@What is observability?](https://www.youtube.com/watch?v=--17See0KHs) +- [@video@Monitoring vs Observability](https://www.youtube.com/watch?v=b6yWa3V2iBQ) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/orchestration--deployment@5VuCUCfb4DEi0HKW11PIX.md b/src/data/roadmaps/mlops/content/orchestration--deployment@5VuCUCfb4DEi0HKW11PIX.md new file mode 100644 index 000000000..72b526eac --- /dev/null +++ b/src/data/roadmaps/mlops/content/orchestration--deployment@5VuCUCfb4DEi0HKW11PIX.md @@ -0,0 +1,8 @@ +# Orchestration & Deployment + +Orchestration and deployment involve automating the process of taking a trained machine learning model and making it available for use in a production environment. This includes managing the workflow of model building, testing, and releasing, as well as handling the infrastructure needed to serve the model and scale it to meet demand. It ensures that models are reliably and efficiently integrated into applications and systems. + +Visit the following resources to learn more: + +- [@article@What is orchestration?](https://www.redhat.com/en/topics/automation/what-is-orchestration) +- [@video@What is Data Orchestration?](https://www.youtube.com/watch?v=iyw9puEmTrA) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/orchestration@fes7M--Y8i08_zeP98tVV.md b/src/data/roadmaps/mlops/content/orchestration@fes7M--Y8i08_zeP98tVV.md index c01db57d9..0fcfc18a9 100644 --- a/src/data/roadmaps/mlops/content/orchestration@fes7M--Y8i08_zeP98tVV.md +++ b/src/data/roadmaps/mlops/content/orchestration@fes7M--Y8i08_zeP98tVV.md @@ -4,4 +4,7 @@ ML orchestration refers to the process of managing and coordinating the various Visit the following resources to learn more: -- [@article@ML Observability: what, why, how](https://ubuntu.com/blog/ml-observability) \ No newline at end of file +- [@article@An Introduction to Data Orchestration: Process and Benefits](https://www.datacamp.com/blog/introduction-to-data-orchestration-process-and-benefits) +- [@article@A Complete Guide to Understanding Data Orchestration](https://towardsdatascience.com/a-complete-guide-to-understanding-data-orchestration-87a20b46297c/) +- [@article@Data Orchestration Tools (Quick Reference Guide)](https://www.montecarlodata.com/blog-11-data-orchestration-tools) +- [@video@What is Data Orchestration?](https://www.youtube.com/watch?v=iyw9puEmTrA) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/prometheus@EIjo6iFrU8iDm36_ZtaW5.md b/src/data/roadmaps/mlops/content/prometheus@EIjo6iFrU8iDm36_ZtaW5.md new file mode 100644 index 000000000..bd1fe9e7f --- /dev/null +++ b/src/data/roadmaps/mlops/content/prometheus@EIjo6iFrU8iDm36_ZtaW5.md @@ -0,0 +1,10 @@ +# Prometheus + +Prometheus is an open-source monitoring and alerting toolkit originally built at SoundCloud. It collects and stores metrics as time-series data, meaning metrics are stored with a timestamp at which they were recorded, along with optional key-value pairs called labels. Prometheus uses a pull model to scrape metrics from instrumented jobs, either directly or via push gateways for short-lived jobs. It offers a powerful query language (PromQL) to analyze and visualize the collected data, enabling users to set up alerts based on defined thresholds. + +Visit the following resources to learn more: + +- [@official@Prometheus Website](https://prometheus.io/) +- [@official@Prometheus Docs](https://prometheus.io/docs/introduction/overview/) +- [@official@Getting Started with Prometheus](https://prometheus.io/docs/tutorials/getting_started/) +- [@video@Introduction to the Prometheus Monitoring System | Key Concepts and Features](https://www.youtube.com/watch?v=STVMGrYIlfg&t=16s) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/pytorch-mobile@qyNOEqp7hW_P7-Isz_v4o.md b/src/data/roadmaps/mlops/content/pytorch-mobile@qyNOEqp7hW_P7-Isz_v4o.md new file mode 100644 index 000000000..6cc7d7859 --- /dev/null +++ b/src/data/roadmaps/mlops/content/pytorch-mobile@qyNOEqp7hW_P7-Isz_v4o.md @@ -0,0 +1,10 @@ +# PyTorch Mobile + +PyTorch Mobile is a framework that allows you to run PyTorch models directly on mobile devices, like smartphones and tablets. It enables on-device machine learning inference, meaning the model computations happen locally without needing a network connection to a remote server. This offers benefits like reduced latency, increased privacy, and the ability to function offline. + +Visit the following resources to learn more: + +- [@official@Welcome to the ExecuTorch Documentation](https://docs.pytorch.org/executorch/stable/index.html) +- [@opensource@executorch](https://github.com/pytorch/executorch) +- [@video@ExecuTorch 1.0: General Availability Status for Mobile and Embedded...- Mergen Nachin & Cemal Bilgin](https://www.youtube.com/watch?v=toirKRTLgJA) +- [@video@PyTorch Mobile and Android Neural Networks API | PyTorch Developer Day 2020](https://www.youtube.com/watch?v=B-2spa3UCTU) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/pytorch@Zh7AfH6hJ6MMXiqSnQn7G.md b/src/data/roadmaps/mlops/content/pytorch@Zh7AfH6hJ6MMXiqSnQn7G.md new file mode 100644 index 000000000..8e101fafd --- /dev/null +++ b/src/data/roadmaps/mlops/content/pytorch@Zh7AfH6hJ6MMXiqSnQn7G.md @@ -0,0 +1,11 @@ +# PyTorch + +PyTorch is an open-source machine learning framework primarily developed by Meta AI. It's used for a variety of applications, including computer vision, natural language processing, and reinforcement learning. PyTorch is known for its dynamic computation graph, which allows for more flexibility and easier debugging compared to static graph frameworks. It provides a comprehensive set of tools and libraries to build and train neural networks. + +Visit the following resources to learn more: + +- [@official@PyTorch](https://pytorch.org/) +- [@official@PyTorch Docs](https://pytorch.org/docs/stable/index.html) +- [@article@What is PyTorc? | IBM](https://www.ibm.com/think/topics/pytorch) +- [@video@PyTorch in 100 seconds](https://www.youtube.com/watch?v=ORMx45xqWkA) +- [@video@PyTorch for Deep Learning & Machine Learning – Full Course](https://www.youtube.com/watch?v=V_xro1bcAuA) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/scikit-learn@T-pybEZVvvXopCTbDykR-.md b/src/data/roadmaps/mlops/content/scikit-learn@T-pybEZVvvXopCTbDykR-.md new file mode 100644 index 000000000..1be49cca5 --- /dev/null +++ b/src/data/roadmaps/mlops/content/scikit-learn@T-pybEZVvvXopCTbDykR-.md @@ -0,0 +1,12 @@ +# Scikit-learn + +Scikit-learn is a Python library that provides simple and efficient tools for data mining and data analysis. It features various classification, regression, clustering algorithms, and tools for model selection, preprocessing, and dimensionality reduction. It's built on NumPy, SciPy, and matplotlib, making it a robust and versatile library for a wide range of machine learning tasks. + +Visit the following resources to learn more: + +- [@official@scikit-learn: machine learning in Python](https://scikit-learn.org/) +- [@opensource@scikit-learn](https://github.com/scikit-learn/scikit-learn) +- [@article@What is Scikit-Learn (Sklearn)?](https://www.ibm.com/think/topics/scikit-learn) +- [@article@Read Articles about scikit-learn](https://towardsdatascience.com/tag/sklearn/) +- [@video@How to train and test a neural network using scikit-learn and Keras in Jupyter Notebook](https://www.youtube.com/watch?v=_JG71FIP1rk) +- [@video@Scikit-learn Crash Course - Machine Learning Library for Python](https://www.youtube.com/watch?v=0B5eIE_1vpU) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/shap@JQKEWz0-vIJoLimLKvIzz.md b/src/data/roadmaps/mlops/content/shap@JQKEWz0-vIJoLimLKvIzz.md new file mode 100644 index 000000000..9948e4ec1 --- /dev/null +++ b/src/data/roadmaps/mlops/content/shap@JQKEWz0-vIJoLimLKvIzz.md @@ -0,0 +1,10 @@ +# SHAP + +SHAP (SHapley Additive exPlanations) is a method used to explain the output of any machine learning model. It uses concepts from game theory to assign each feature a value representing its contribution to the prediction. These values, known as SHAP values, indicate the degree to which each feature contributed to the model's output for a specific instance, facilitating a deeper understanding of the model's decision-making process. + +Visit the following resources to learn more: + +- [@official@Welcome to the SHAP documentation](https://shap.readthedocs.io/en/latest/) +- [@opensource@shap](https://github.com/shap/shap) +- [@article@Explainable AI - Understanding and Trusting Machine Learning Models](https://www.datacamp.com/tutorial/explainable-ai-understanding-and-trusting-machine-learning-models) +- [@video@SHAP values for beginners | What they mean and their applications](https://www.youtube.com/watch?v=MQ6fFDwjuco) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/spark@UljuqA89_SlCSDWWMD_C_.md b/src/data/roadmaps/mlops/content/spark@UljuqA89_SlCSDWWMD_C_.md index 3fe6e9603..9101e8636 100644 --- a/src/data/roadmaps/mlops/content/spark@UljuqA89_SlCSDWWMD_C_.md +++ b/src/data/roadmaps/mlops/content/spark@UljuqA89_SlCSDWWMD_C_.md @@ -6,4 +6,6 @@ Visit the following resources to learn more: - [@official@ApacheSpark](https://spark.apache.org/documentation.html) - [@article@Spark By Examples](https://sparkbyexamples.com) -- [@feed@Explore top posts about Apache Spark](https://app.daily.dev/tags/spark?ref=roadmapsh) \ No newline at end of file +- [@article@First Steps in Machine Learning with Apache Spark](https://towardsdatascience.com/first-steps-in-machine-learning-with-apache-spark-672fe31799a3/) +- [@article@Read articles about Apache Spark](https://towardsdatascience.com/tag/apache-spark/) +- [@video@Apache Spark Architecture - EXPLAINED!](https://www.youtube.com/watch?v=iXVIPQEGZ9Y) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/sql@51x_5z0pHTE_yZoyvFUBy.md b/src/data/roadmaps/mlops/content/sql@51x_5z0pHTE_yZoyvFUBy.md new file mode 100644 index 000000000..8bf3a905d --- /dev/null +++ b/src/data/roadmaps/mlops/content/sql@51x_5z0pHTE_yZoyvFUBy.md @@ -0,0 +1,11 @@ +# SQL + +SQL, or Structured Query Language, is a standard language for managing and manipulating data held in relational database management systems (RDBMS). It allows users to define, access, and control data, enabling operations like creating databases, inserting, updating, deleting, and retrieving data based on specific criteria. SQL provides a structured way to interact with databases, ensuring data integrity and consistency. + +Visit the following resources to learn more: + +- [@official@Visit the Dedicated SQL Roadmap](https://roadmap.sh/sql) +- [@course@Premium SQL Course - Roadmap](https://roadmap.sh/courses/sql) +- [@article@SQL Tutorial](https://www.w3schools.com/sql/) +- [@article@How I Learned SQL In 2 Weeks (From Scratch)](https://towardsdatascience.com/how-i-learned-sql-in-2-weeks-from-scratch-b78040f4e2c1/) +- [@video@Full SQL Crash Course - Learn SQL in 90 Minutes](https://www.youtube.com/watch?v=7cIG41gjHB4) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/tensorflow@so5IQDxKibaZlgoCh8tpQ.md b/src/data/roadmaps/mlops/content/tensorflow@so5IQDxKibaZlgoCh8tpQ.md new file mode 100644 index 000000000..4bd93084f --- /dev/null +++ b/src/data/roadmaps/mlops/content/tensorflow@so5IQDxKibaZlgoCh8tpQ.md @@ -0,0 +1,9 @@ + + +Visit the following resources to learn more: + +- [@official@Tensorflow](https://www.tensorflow.org/) +- [@official@Tensorflow Documentation](https://www.tensorflow.org/learn) +- [@article@astering Deep Learning with TensorFlow: From Beginner to Expert](https://towardsdatascience.com/an-introduction-to-tensorflow-fa5b17051f6b/) +- [@video@Tensorflow in 100 seconds](https://www.youtube.com/watch?v=i8NETqtGHms) +- [@video@Python TensorFlow for Machine Learning – Neural Network Text Classification Tutorial](https://www.youtube.com/watch?v=VtRLrQ3Ev-U) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/terraform@dA9AE-3lTB6lN-X-_Byd2.md b/src/data/roadmaps/mlops/content/terraform@dA9AE-3lTB6lN-X-_Byd2.md new file mode 100644 index 000000000..375e0db72 --- /dev/null +++ b/src/data/roadmaps/mlops/content/terraform@dA9AE-3lTB6lN-X-_Byd2.md @@ -0,0 +1,11 @@ +# Terraform + +Terraform is an open-source infrastructure as code (IaC) tool that allows you to define and provision infrastructure using a declarative configuration language. It enables you to manage infrastructure resources across various cloud providers and on-premises environments in a consistent and automated manner. Terraform uses a state file to track the current configuration of your infrastructure, allowing you to plan and apply changes safely and predictably. + +Visit the following resources to learn more: + +- [@roadmap@Visit the Dedicated Terraform Roadmap](https://roadmap.sh/terraform) +- [@official@Terraform](https://developer.hashicorp.com/terraform) +- [@article@What is Terraform?](https://www.ibm.com/think/topics/terraform) +- [@article@Automatically Managing Data Pipeline Infrastructures With Terraform](https://towardsdatascience.com/automatically-managing-data-pipeline-infrastructures-with-terraform-323fd1808a47/) +- [@video@Terraform Course - Automate your AWS cloud infrastructure](https://www.youtube.com/watch?v=SLB_c_ayRMo) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/tflite@YFo3NnwVst5EBTtLR-cJ1.md b/src/data/roadmaps/mlops/content/tflite@YFo3NnwVst5EBTtLR-cJ1.md new file mode 100644 index 000000000..bf8a48cbc --- /dev/null +++ b/src/data/roadmaps/mlops/content/tflite@YFo3NnwVst5EBTtLR-cJ1.md @@ -0,0 +1,10 @@ +# TFLite + +TFLite is a lightweight version of TensorFlow, designed for running machine learning models on mobile, embedded, and IoT devices. It enables on-device inference, meaning models can be executed directly on the device without needing a network connection or relying on cloud-based processing. This reduces latency, improves privacy, and allows for offline functionality. + +Visit the following resources to learn more: + +- [@official@TensorFLow LIte](https://www.tensorflow.org/lite/guide) +- [@article@TensorFlow Lite Tutorial: How to Get Up and Running](https://www.influxdata.com/blog/tensorflow-lite-tutorial-how-to-get-up-and-running/) +- [@video@TensorFlow Lite for Edge Devices - Tutorial](https://www.youtube.com/watch?v=OJnaBhCixng) +- [@video@TensorFlow Lite in Android with Google Play services](https://www.youtube.com/watch?v=SEeEsbWZog8&list=PLQY2H8rRoyvwhLghMaygIJS0_f_blnUlJ) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/version-control-systems@_NPGsGEjcLekjGisdDFWt.md b/src/data/roadmaps/mlops/content/version-control-systems@_NPGsGEjcLekjGisdDFWt.md new file mode 100644 index 000000000..3822ada9e --- /dev/null +++ b/src/data/roadmaps/mlops/content/version-control-systems@_NPGsGEjcLekjGisdDFWt.md @@ -0,0 +1,10 @@ +# Version Control Systems + +Version control systems are tools that track changes to files over time. They allow multiple people to work on the same project simultaneously without overwriting each other's work. These systems record a history of modifications, enabling users to revert to previous versions, compare changes, and understand who made specific alterations and when. + +Visit the following resources to learn more: + +- [@roadmap@Visit Dedicated Git & GitHub Roadmap](https://roadmap.sh/git-github) +- [@official@Git Documentation](https://git-scm.com/docs) +- [@article@Learn Git by Atlassian](https://www.atlassian.com/git) +- [@video@hat is a Version Control System and why you should always use it](https://www.youtube.com/watch?v=IeXhYROClZk) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/version-control@kHDSwlSq8WkLey4EJIQSR.md b/src/data/roadmaps/mlops/content/version-control@kHDSwlSq8WkLey4EJIQSR.md index 3e4890d1f..92258a964 100644 --- a/src/data/roadmaps/mlops/content/version-control@kHDSwlSq8WkLey4EJIQSR.md +++ b/src/data/roadmaps/mlops/content/version-control@kHDSwlSq8WkLey4EJIQSR.md @@ -4,7 +4,9 @@ Version control is a system that records changes to a file or set of files over Visit the following resources to learn more: +- [@roadmap@Visit the Dedicated Git & GitHub Roadmpa](https://roadmap.sh/git-github) - [@official@Git](https://git-scm.com/) - [@official@Git Documentation](https://git-scm.com/docs) - [@article@What is Version Control?](https://www.atlassian.com/git/tutorials/what-is-version-control) +- [@article@Getting Started with Git and GitHub: A Complete Tutorial for Beginner](https://towardsdatascience.com/learn-basic-git-commands-for-your-data-science-works-2a75396d530d/) - [@feed@Explore top posts about Version Control](https://app.daily.dev/tags/version-control?ref=roadmapsh) \ No newline at end of file diff --git a/src/data/roadmaps/mlops/content/what-is-mlops@IghGpwAFVB067uOosmoDC.md b/src/data/roadmaps/mlops/content/what-is-mlops@IghGpwAFVB067uOosmoDC.md new file mode 100644 index 000000000..0fff68d21 --- /dev/null +++ b/src/data/roadmaps/mlops/content/what-is-mlops@IghGpwAFVB067uOosmoDC.md @@ -0,0 +1,14 @@ +# What is MLOps? + +MLOps, short for Machine Learning Operations, is a set of practices that aims to reliably and efficiently deploy and maintain machine learning models in production. It bridges the gap between model development (Data Scientists) and model deployment (Operations), emphasizing automation, monitoring, and collaboration throughout the entire machine learning lifecycle. Think of it as DevOps, but specifically tailored for the unique challenges of machine learning. + +Visit the following resources to learn more: + +- [@article@What is MLOps?](https://aws.amazon.com/what-is/mlops/) +- [@article@MLOps Explained: A Deep Dive into Machine Learning Operations](https://hermanmotcheyo.medium.com/mlops-explained-a-deep-dive-into-machine-learning-operations-ab9342c5c90d) +- [@article@MLOps vs DevOps: Differences, Overlaps, and Use Cases](https://www.datacamp.com/blog/mlops-vs-devops) +- [@article@Machine Learning Operations (MLOps) For Beginners](https://towardsdatascience.com/machine-learning-operations-mlops-for-beginners-a5686bfe02b2/) +- [@article@MLOps: What It Is, Why It Matters, and How to Implement It](https://neptune.ai/blog/mlops) +- [@book@MLOps Engineering at Scale - Carl Osipov](http://103.203.175.90:81/fdScript/RootOfEBooks/E%20Book%20collection%20-%202025%20-%20C/CSE%20%20IT%20AIDS%20ML/MLOps%20Engineering%20at%20Scale%20-%20Carl%20Osipov%20(Manning,%202022).pdf) +- [@video@What is MLOps?](https://www.youtube.com/watch?v=OejCJL2EC3k) +- [@video@MLOps Explained - What It Is, Why You Need It and How It Works](https://www.youtube.com/watch?v=biqYkVf-a7Y) \ No newline at end of file