- How to find the optimum parameter values for a curve fitting problem. Stochastic Gradient Descent Method for Finding Local Optimum.
This is a commonly used numerical optimization technique. Some times, this is also called batch gradient descent algorithm.
2. How to avoid over-fitting problem? Use Regularization.
3. Sparse Matrix Based Prediction – GLMNET in R
4. Naive Bayes Modeling when there are many many conditioning variables
5. Out of Necessity, Real Time Application of Naive Bayes Application – Spam Deduction
6. Fisher LDA and Bayesian Classification
7.Lagrange Multipliers – A Simple Intro
8. Density Based Spacial Clutering Algorithm With Noise – DBSCAN
9. Meanshift Clustering with Scikit-learn and Python