Notes
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Notes on ML, DL & CS
DL
6
Math
2
ML
9
Algorithms
2
DL
0. Backpropagation in neural networks. Activation functions.
Dec 23, 2019
1. Gradient descent and optimization in neural networks
Dec 23, 2019
2. Regularization in neural networks
Dec 23, 2019
3. Convolution types: transposed convolution and dilated convolution
Dec 21, 2019
4. Popular architectures
Jan 7, 2020
5. Recurrent neural networks
Jan 25, 2020
Math
0. Basics of statistics
Feb 3, 2020
1. Refresher notes: Probability distributions
Feb 3, 2020
ML
0. Fundamentals
Feb 10, 2020
1. Linear Regression
Dec 21, 2019
2. Logistic Regression
Dec 21, 2019
3. Support Vector Machines
Dec 21, 2019
4. Decision Trees
Dec 21, 2019
5. Random Forests
Jan 2, 2020
6. Boosting and Additive Trees. AdaBoost.
Jan 2, 2020
7. Gradient Boosting Machine
Jan 4, 2020
8. Singular Value Decomposition (SVD). Principal Component Analysis (PCA).
Jan 3, 2020
Algorithms
1. Problem solving approach: stack and queue
Dec 19, 2019
2. Problem solving approach: heap
Jan 10, 2020