thumbnail
Data Science

Machine Learning Green Belt

Reviews 5.00 (2 Reviews)

Course Overview

This course helps building a strong background in Machine Learning for individuals with no prior experience. You will learn the basics of Machine Learning, including supervised and unsupervised learning, and how to apply them to real-world problems. Using Python and popular Machine Learning libraries such as Scikit-Learn, you will learn how to preprocess data, build models, and evaluate their performance. By the end of this course, you will have a solid understanding of Machine Learning concepts and techniques, and be able to apply them to your own projects.

Note: You will get this course added to course dashboard in your account after completing the purchase.

Avail 50% discount on this course until August 15th 2023. Use coupon code AI50.

What You'll Learn?

  • Understand the basics of Machine Learning.
  • Identify the differences between supervised and unsupervised learning.
  • Apply Scikit-Learn to preprocess data and build models.
  • Evaluate the performance of Machine Learning models.
  • Apply Machine Learning techniques to real-world problems.
  • Beginners
  • Basic knowledge of programming in Python is recommended but not required. No prior experience with Machine Learning is needed.
  • Python notebooks to practice codes
  • Video Lessons
  • Handouts
  • Auto-generated Certificate of Completion
  • Well designed certificate on request

Course Content

  • Getting Familiar with Machine Learning
    • Getting Familiar with Machine Learning

    • Introduction and Overviews

    • AI and Machine Learning

    • Need for Machine Learning

    • Applications of Machine Learning

  • Getting Started with Machine Learning
    • Overview

    • What is Machine Learning?

    • Supervised and Unsupervised Learning

    • Techniques of Supervised Learning

    • Techniques of Unsupervised Learning

    • Video Tutorial - Machine Learning Intuition

      00:08:29
  • Supervised Machine Learning and Classification
    • Supervised Machine Learning

    • Classification

    • Logistic Regression

    • Video Tutorial - Logistic Regression Intuition

      00:08:28
    • Video Tutorial - Logistic Regression Implementation in Python

      00:04:25
    • Decision Tree

    • Video Tutorial - Decision Tree Intuition

      00:06:07
    • Video Tutorial - Deicsion Tree Implementation in Python

      00:02:34
    • Random Forest

    • Video Tutorial - Random Forest Intuition

      00:06:36
    • Video Tutorial - Random Forest Implementation in Python

      00:01:59
    • K-Nearest Neighbours

    • Video Tutorial - K-Nearest Neighbours Intuition

      00:04:47
    • Video Tutorial - K-NN Implementation in Python

      00:04:32
    • Naive Bayes

    • Video Tutorial - Naive Bayes Intuition

      00:05:04
    • Video Tutorial - Naive Bayes Classification in Python

      00:02:40
    • Support Vector Machine

      00:16:52
    • Video Tutorial - Support Vector Machine Intuition

      00:04:21
    • Video Tutorial - SVM Classification Implementation in Python

      00:02:33
    • Classification Evaluation Metrics

    • Coding Practice - Classification Algorithms

  • Regression Analysis
    • Overview

    • Simple Linear Regression

    • Video Tutorial - Simple Linear Regression Intuition

      00:13:42
    • Video Tutorial - Simple Linear Regression Implementation in Python

      00:03:41
    • Multiple Linear Regression

    • Video Tutorial - Multiple Linear Regression Intuition

      00:05:24
    • Video Tutorial - Multiple Linear Regression Implementation in Python

      00:03:24
    • Decision Tree Regression

    • Video Tutorial - Decision Tree Regression Intuition

      00:05:02
    • Video Tutorial - Deicsion Tree Regression Implementation in Python

      00:02:15
    • Random Forest Regression

    • Video Tutorial - Random Frest Regression Intuition

      00:04:03
    • Video Tutorial - Random Forest Regression Implementation in Python

      00:03:23
    • Support Vector Regression

    • Video Tutorial - Support Vector Machine for Regression Intuition

      00:04:46
    • Video Tutorial - Support Vector Machine for Regression in Python

      00:02:59
    • Lasso and Ridge and ElasticNet Regression

    • Video Tutorial - Lasso and Ridge and ElasticNet Regression - Intuition

      00:06:23
    • Video Tutorial - Lasso and Ridge and ElasticNet Regression - Python Implementation

      00:04:37
    • Coding Practice - Regression Algorithms

  • Boosting Techniques
    • Overview

    • Gradient Boosting

    • Video Tutorial - Gradient Boosting Intuition

      00:04:40
    • Video Tutorial - Gradient Boosting Python Implementation

      00:04:56
    • AdaBoost

    • Video Tutorial - AdaBoost Intuition

      00:03:46
    • Video Tutorial - AdaBoost Python Implementation

      00:02:00
    • XGBoost

    • Video Tutorial - XGBoost Intuition

      00:03:27
    • Video Tutorial - XGBoost Python Implementation

      00:02:26
    • Coding Practice - Boosting Algorithms

  • Unsupervised Machine Learning
    • Introduction and Overviews

  • Clustering Techniques
    • Overview

    • K-Means Clustering

    • Video Tutorial - K-Means Clustering Intuition

      00:06:23
    • Video Tutorial - K-Means Clustering Python Implementation

      00:04:08
    • Hierarchical Clustering

    • Video Tutorial - Hierarchical Clustering Intuition

      00:03:58
    • Video Tutorial - Hierarchical Clustering Python Implementation

      00:02:02
    • Coding Practice - Clustering Algorithms

  • Principal Component Analysis
    • Principal Component Analysis

    • Video Tutorial - Principal Component Analysis Intuition

      00:03:00
    • Video Tutorial - PCA Python Implementation

      00:04:54
    • Coding Practice - Principal Component Analysis

  • Anomaly Detection
    • Anomaly Detection and its Techniques

    • Video Tutorial - Anomaly Detection Intuition

      00:04:34
    • Video Tutorial - Anomaly Detection Python Implementation

      00:01:46
    • Coding Practice - Anomaly Detection Algorithms

  • Artificial Neural Networks
    • Introduction and Overviews

    • ANN Architectures and Their Working

    • Video Tutorial - Introduction to Neural Networks

      00:07:48
    • ANN for Classification

    • Video Tutorial - ANN for Classification Intuition

      00:02:37
    • Video Tutorial - ANN for Classification Python Implementation

      00:06:41
    • ANN for Regression

    • Video Tutorial - ANN for Regression Intuition

      00:02:37
    • Video Tutorial - ANN for Regression Python Implementation

      00:02:59
    • Coding Practice - Artificial Neural Network

  • Handouts
    • Handouts - Reference Material, Codes, Notebook Links

Original price was: ₹4,222.00.Current price is: ₹845.00.
  • Duration 15:00:00
  • Lessons 92
  • Enrolled 2
  • Language English
  • Skill Beginner
  • Available Seats 498
  • Last Update November 18, 2023