Machine Learning Training Chennai

Module 1

Introduction to Machine Learning

Introduction to Statistics

Hypothesis Space and Inductive Bias

Evaluation and cross-validation

Hands-On I

Module 2

Linear Regression

Decision Trees

Learning Decision Trees


Python Hands-On for Linear Regression and Decision Trees

Hands-On II

Module 3

Bayesian Learning

Naive Bayes

Bayesian Network

Python Hands-on for Naive Bayes

Hands-On III

Module 4

k-Nearest Neighbour

Feature Selection

Feature Extraction

Colloborative Filtering

Python Hands-On for KNN and PCA

Hands-On IV

Module 5

Logistic Regression

Support Vector Machine (SVM)

Dual Formation

Maximum Margin with Noise

Nonlinear SVM and Kennel Function

Solution to the Dual Problem

Python Hands-On for SVM

Module 6

Introduction to Neural Network

Multilayer Neural Network

Neural Network and Backpropagation Algorithm

Deep Neural Network

Python Hands-On for Neural Network

Hands-On VI

Module 7

Computational Learning Theory

Finite Hypothesis Space

VC Dimension

Introduction to Ensembles

Bagging and Boosting

Module 8

Clustering Introduction

Kmeans Clustering

Agglomerative Hierarchical Clustering

Python Hands-On for Kmeans Clustering