Machine Learning Certification Training

Session 1 Introduction:–

What is Machine Learning?

Applications of Machine Learning

ML Types of Learning- Supervised vs Unsupervised Learning

Python libraries suitable for Machine Learning

Session 2 Data Pre-processing:–

Missing Value

Categorical Data

Splitting Dataset

Feature Scaling

Session 3 Regression:–

Introduction to Regression

Types of Regression

Simple Linear Regression

Multiple Linear Regression

Polynomial Regression

Decision Tree Regression

Random Forest Regression

Session 4 Classification:–

Basic Concept of Classification

Classification vs Regression

Logistic Regression

K-NN

SVM

Kernel SVM

Naive Bayes

Decision Tree Classification

Random Forest Classification

Session 5 Clustering: –

K-Means

Hierarchical Clustering

Session 6 Natural Language Processing: –

NLTK installation

Tokenization

Case Study: Document Classification

Session 7 Deep Learning:–

Artificial Neural Networks

Convolutional Neural Networks

Session 8 Dimensionality Reduction:–

Introduction to Dimensionality Reduction

Principal Component Analysis (PCA)

LDA

Kernel PCA