diff --git a/src/data/roadmaps/machine-learning/content/back-propagation@0meihv22e11GwqnRdSJ9g.md b/src/data/roadmaps/machine-learning/content/back-propagation@0meihv22e11GwqnRdSJ9g.md index 306b96788..312416b69 100644 --- a/src/data/roadmaps/machine-learning/content/back-propagation@0meihv22e11GwqnRdSJ9g.md +++ b/src/data/roadmaps/machine-learning/content/back-propagation@0meihv22e11GwqnRdSJ9g.md @@ -1,3 +1 @@ -# Backpropagation - -Backpropagation is a fundamental algorithm used to train artificial neural networks. It works by calculating the gradient of the loss function with respect to the network's weights. This gradient is then used to adjust the weights, iteratively reducing the error between the network's predictions and the actual target values. In essence, it's a method for efficiently computing how much each weight in the network contributed to the overall error, allowing for targeted adjustments to improve performance. \ No newline at end of file +# Back Propagation \ No newline at end of file diff --git a/src/data/roadmaps/machine-learning/content/lasso@EXogp25SPW1bBfb1gRDAe.md b/src/data/roadmaps/machine-learning/content/lasso@EXogp25SPW1bBfb1gRDAe.md index d78f2d4a2..e50ca9023 100644 --- a/src/data/roadmaps/machine-learning/content/lasso@EXogp25SPW1bBfb1gRDAe.md +++ b/src/data/roadmaps/machine-learning/content/lasso@EXogp25SPW1bBfb1gRDAe.md @@ -6,4 +6,4 @@ Visit the following resources to learn more: - [@article@Lasso | scikit-learn](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Lasso.html) - [@article@What is lasso regression?](https://www.ibm.com/think/topics/lasso-regression) -- [@video@Lasso Regression with Scikit-Learn (Beginner Friendly)](https://www.youtube.com/watch?v=LmpBt0tenJE) \ No newline at end of file +- [@video@Lasso Regression with Scikit-Learn (Beginner Friendly)](https://www.youtube.com/watch?v=LmpBt0tenJE) diff --git a/src/data/roadmaps/machine-learning/content/matrix--matrix-operations@1IhaXJxNREq2HA1nT-lMM.md b/src/data/roadmaps/machine-learning/content/matrix--matrix-operations@1IhaXJxNREq2HA1nT-lMM.md index db82577cd..adbdd3b7a 100644 --- a/src/data/roadmaps/machine-learning/content/matrix--matrix-operations@1IhaXJxNREq2HA1nT-lMM.md +++ b/src/data/roadmaps/machine-learning/content/matrix--matrix-operations@1IhaXJxNREq2HA1nT-lMM.md @@ -5,4 +5,4 @@ A matrix is a rectangular array of numbers, symbols, or expressions, arranged in Visit the following resources to learn more: - [@article@Matrix (mathematics)](https://en.wikipedia.org/wiki/Matrix_(mathematics)) -- [@video@Linear Algebra - Matrix Operations](https://www.youtube.com/watch?v=p48uw2vFWQs) \ No newline at end of file +- [@video@Linear Algebra - Matrix Operations](https://www.youtube.com/watch?v=p48uw2vFWQs) diff --git a/src/data/roadmaps/machine-learning/content/probability@tP0oBkjvJC9hrtARkgLon.md b/src/data/roadmaps/machine-learning/content/probability@tP0oBkjvJC9hrtARkgLon.md index 16c0fafc5..b5444bf1b 100644 --- a/src/data/roadmaps/machine-learning/content/probability@tP0oBkjvJC9hrtARkgLon.md +++ b/src/data/roadmaps/machine-learning/content/probability@tP0oBkjvJC9hrtARkgLon.md @@ -1 +1,9 @@ -# Linear Algebra \ No newline at end of file +# Probability + +Probability is a way to quantify the likelihood of an event occurring. It provides a numerical measure, ranging from 0 to 1, that represents the likelihood of a specific outcome occurring. A probability of 0 indicates impossibility, while a probability of 1 signifies certainty. It's a fundamental concept for understanding uncertainty and making predictions based on available data. + +Visit the following resources to learn more: + +- [@book@Probability and Statistics: The Science of Uncertainty](https://utstat.utoronto.ca/mikevans/jeffrosenthal/book.pdf) +- [@article@Probability for machine learning](https://towardsdatascience.com/probability-for-machine-learning-b4150953df09/) +- [@video@Probability for Data Science & Machine Learning](https://www.youtube.com/watch?v=sEte4hXEgJ8) \ No newline at end of file diff --git a/src/data/roadmaps/machine-learning/content/validation-techniques@0hi0LdCtj9Paimgfc-l1O.md b/src/data/roadmaps/machine-learning/content/validation-techniques@0hi0LdCtj9Paimgfc-l1O.md index d01bd3065..6a3dd4531 100644 --- a/src/data/roadmaps/machine-learning/content/validation-techniques@0hi0LdCtj9Paimgfc-l1O.md +++ b/src/data/roadmaps/machine-learning/content/validation-techniques@0hi0LdCtj9Paimgfc-l1O.md @@ -7,4 +7,4 @@ Visit the following resources to learn more: - [@article@Cross-validation: evaluating estimator performance | scikit-learn](https://scikit-learn.org/stable/modules/cross_validation.html) - [@article@The 5 Stages of Machine Learning Validation](https://towardsdatascience.com/the-5-stages-of-machine-learning-validation-162193f8e5db/) - [@article@What is the Difference Between Test and Validation Datasets?](https://machinelearningmastery.com/difference-test-validation-datasets/) -- [@video@Validating Machine Learning Model and Avoiding Common Challenges](%5Bhttps://www.youtube.com/watch?v=TnIh2b2Rw6%5D(https://www.youtube.com/watch?v=TnIh2b2Rw6Y)) \ No newline at end of file +- [@video@Validating Machine Learning Model and Avoiding Common Challenges]([https://www.youtube.com/watch?v=TnIh2b2Rw6](https://www.youtube.com/watch?v=TnIh2b2Rw6Y))