Blog Post Ideas
Published on 18 Mar 2017
1. Why bias term in neural networks? Illustrate with a simple 2 class problem in two dimensions.
2. Loss functions - use a squared error loss such that it is hinged (set to 0) if \\( ty > 1 \\). What kind of classifier it leads to. (Less robust to outliers). Demonstrate with a sample dataset.
3. Ho Kashyap algorithm
4. Spectral clustering and tip on number of isolated components
5. EM algorithm for multiple regressions (already have the ipython notebook)
6. Backpropagation - vectorized implementation
7. SVM - solving dual vs primal
8. Proof of chain rule in backprop
9. Influence of \\( \eta \\), the learning rate on neural network learning
10. What is stochastic gradient descent?
11. sklearn custom estimator - also include my codes for perceptron, neural net & naive bayes
12. ReLU activation function - implement a neural network with ReLU
14. MRF simple image denoising
15. Implement violat jones + adaboost
16. A new perspective on PCA - \\( min ||x - UU^Tx||^2 \\) with the constraint \\( UU^T=I \\)
17. Brown Clustering vs Word embeddings
18. SVM Dual Visualization - https://www.youtube.com/watch?v=ztCXSAUAe38