machine learning ml

Text editor/IDE options.. (don’t settle with notepad) • PyCharm (IDE) • Visual Studio Code (IDE) • Sublime Text (IDE) • Atom • Notepad ++/gedit • Vim (for Linux)

Deep Learning Supervised learning with non linear models Logistic Regression Neural Networks computational power data available algorithms Propagation equation

Deep Learning Supervised Learning with Non-linear Models Neural Networks Backpropagation Vectorization Over Training Examples

summary of Kernel Methods SVMs

Kernels. SVM.

1 Definition 2 Gaussian facts 3 Closure properties 4 Summary 5 Exercise

Outline Naive Bayes Laplacesmoothing Event Models Kernel Methods

Gaussian discriminant analysis & it is model Naive Bayes.

Outline 1 Basics 2 Random Variables 3 Expectation-Variance 4 Joint Distributions 5 Covariance 6 RV Conditionals 7 Random Vectors 8 Multivariate Gaussian