Machine Learning Certification Training 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

 

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