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25 Days Of ML

Day 1, 2: Nov 4, Nov 5, 2019

Today's Progress: Learned data preprocessing.

Thoughts: Simple stuff which is really important.

Link of Work: Commit

Day 3: Nov 6, 2019

Today's Progress: Learned simple linear regression.

Thoughts: -

Link of Work: Commit

Day 4: Nov 7, 2019

Today's Progress: Learned multiple linear regression and backward elimination method.

Thoughts: -

Link of Work: Commit

Day 5, 6: Nov 8, Nov 9, 2019

Today's Progress: Learned polynomial regression.

Thoughts: -

Link of Work: Commit

Day 7: Nov 10, 2019

Today's Progress: Learned support vector regression.

Thoughts: -

Link of Work: Commit

Day 8, Day 9: Nov 11, Nov 12, 2019

Today's Progress: Learned decision tree regression and concept of bias and variance

Thoughts: Best explanation I could find for regression trees https://www.youtube.com/watch?v=g9c66TUylZ4

Day 10: Nov 13, 2019

Today's Progress: Learned random forest regression

Thoughts: -

Day 11, Day 12: Nov 14, Nov 15, 2019

Today's Progress: Learned logistic regression and visualize it using confusion matrix

Thoughts: -

Day 13: Nov 16, 2019

Today's Progress: Learned k-nearest neighbors and to calculate euclidean distance

Thoughts: -

Day 14, Day 15, Day 16: Nov 17, Nov 18, Nov 19, 2019

Today's Progress: Learned support vector machine using different types of kernel and mapping in higher dimension

Thoughts: -

Day 17, Day 18: Nov 20, Nov 21, 2019

Today's Progress: Learned bayes theorem and naive bayes

Thoughts: -

Day 19, Day 20: Nov 22, Nov 23, 2019

Today's Progress: Learned decision tree classification Thoughts: -

Day 21: Nov 24, 2019

Today's Progress: Learned random forest classification

Thoughts: -

Day 22: Nov 25, 2019

Today's Progress: Learned to evaluate classification model performance

Thoughts: -

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