Course Syllabus

MACHINE LEARNING COURSE HIGHLIGHTS

Machine Learning has been gaining popularity for quite some time and is currently in high-demand. Machine Learning is an exciting career path for both freshers and experienced individuals.


Supervised

Unsupervised

Reinforcement


Regression

Linear Regression

Logistic Regression


Into

Types

Algorithm

Implementation


Into

Algorithm

Hyperplane and kernels


Random Forest

Theory

Algorithm

Entropy and Decision Tree

Classification


Intro

Theory of Classification

Bayes Theorem

Algorithm

Limitations, Practical Applications


Theory

Algorithm

Distance Functions

Euclidean

Hamming

Minkowski

Practical application


Intro

Types of boosting

Gradient descent

Practical application


Intro

Concepts

NLP (Natural Language  Processing)

Practical Application


Intro

Artificial Neural Network(ANN)

Feature Learning and Engineering