Machine Learning

General Information

Fee : 10500/-

Description

Machine Learning can be an incredibly beneficial tool to uncover hidden insights and predict future trends.
This Machine Learning with Python course will give you all the tools you need to get started with supervised and unsupervised learning.

Expectations and Goals

This Machine Learning with Python course dives into the basics of machine learning using an approachable, and well-known, programming languagei.e python. You’ll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each.

Course Materials

Optional Materials

  • Internet Connection

Course Syllabus

Module 1 – Supervised vs Unsupervised Learning

Machine Learning vs Statistical Modelling
Supervised vs Unsupervised Learning
Supervised Learning Classification
Unsupervised Learning

Module 2 – Supervised Learning I

K-Nearest Neighbors
Decision Trees
Random Forests
Reliability of Random Forests
Advantages & Disadvantages of Decision Trees

Module 3 – Supervised Learning II

Regression Algorithms
Model Evaluation
Model Evaluation: Overfitting &Underfitting
Understanding Different Evaluation Models

Module 4 – Unsupervised Learning

K-Means Clustering plus Advantages & Disadvantages
Hierarchical Clustering plus Advantages & Disadvantages
Measuring the Distances Between Clusters – Single Linkage Clustering
Measuring the Distances Between Clusters – Algorithms for Hierarchy Clustering
Density-Based Clustering

Module 5 – Dimensionality Reduction & Collaborative Filtering

Dimensionality Reduction: Feature Extraction & Selection
Collaborative Filtering & Its Challenges

Project

Exam Schedule

After the Completion of All Modules of Training

Apply for Machine Learning