Machine Learning Green Belt

Instructor

Ambilio Incubity

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

Machine Learning Green Belt

Ambilio Incubity

Course Overview

What You'll Learn?

Course Content

Getting Familiar with Machine Learning

Introduction and Overviews

AI and Machine Learning

Need for Machine Learning

Applications of Machine Learning

Overview

What is Machine Learning?

Supervised and Unsupervised Learning

Techniques of Supervised Learning

Techniques of Unsupervised Learning

Video Tutorial - Machine Learning Intuition

Supervised Machine Learning

Classification

Logistic Regression

Video Tutorial - Logistic Regression Intuition

Video Tutorial - Logistic Regression Implementation in Python

Decision Tree

Video Tutorial - Decision Tree Intuition

Video Tutorial - Deicsion Tree Implementation in Python

Random Forest

Video Tutorial - Random Forest Intuition

Video Tutorial - Random Forest Implementation in Python

K-Nearest Neighbours

Video Tutorial - K-Nearest Neighbours Intuition

Video Tutorial - K-NN Implementation in Python

Naive Bayes

Video Tutorial - Naive Bayes Intuition

Video Tutorial - Naive Bayes Classification in Python

Support Vector Machine

Video Tutorial - Support Vector Machine Intuition

Video Tutorial - SVM Classification Implementation in Python

Classification Evaluation Metrics

Coding Practice - Classification Algorithms

Overview

Simple Linear Regression

Video Tutorial - Simple Linear Regression Intuition

Video Tutorial - Simple Linear Regression Implementation in Python

Multiple Linear Regression

Video Tutorial - Multiple Linear Regression Intuition

Video Tutorial - Multiple Linear Regression Implementation in Python

Decision Tree Regression

Video Tutorial - Decision Tree Regression Intuition

Video Tutorial - Deicsion Tree Regression Implementation in Python

Random Forest Regression

Video Tutorial - Random Frest Regression Intuition

Video Tutorial - Random Forest Regression Implementation in Python

Support Vector Regression

Video Tutorial - Support Vector Machine for Regression Intuition

Video Tutorial - Support Vector Machine for Regression in Python

Lasso and Ridge and ElasticNet Regression

Video Tutorial - Lasso and Ridge and ElasticNet Regression - Intuition

Video Tutorial - Lasso and Ridge and ElasticNet Regression - Python Implementation

Coding Practice - Regression Algorithms

Overview

Gradient Boosting

Video Tutorial - Gradient Boosting Intuition

Video Tutorial - Gradient Boosting Python Implementation

AdaBoost

Video Tutorial - AdaBoost Intuition

Video Tutorial - AdaBoost Python Implementation

XGBoost

Video Tutorial - XGBoost Intuition

Video Tutorial - XGBoost Python Implementation

Coding Practice - Boosting Algorithms

Introduction and Overviews

Overview

K-Means Clustering

Video Tutorial - K-Means Clustering Intuition

Video Tutorial - K-Means Clustering Python Implementation

Hierarchical Clustering

Video Tutorial - Hierarchical Clustering Intuition

Video Tutorial - Hierarchical Clustering Python Implementation

Coding Practice - Clustering Algorithms

Principal Component Analysis

Video Tutorial - Principal Component Analysis Intuition