Machine Learning Getting Started - 100% Practical Instructor-Led Online Training

Machine Learning Getting Started TOC

You get access to our cloud lab to do all section exercises

Section-1

What is Machine Learning

What is AI
What is Machine Learning?
Types of Machine Learning
Machine Learning Workflow
Machine Learning Life Cycle

Section-2

Introduction to Python and Libraries

Basic Python
Getting Started with Anaconda
NumPy
Pandas
Matplotlib
Sklearn
Seaborn

Section-3

Linear Regression

Correlation Analysis and Feature Selection
Linear Regression with Scikit-Learn
Evaluate Regression Model Performance
Dealing with Non-linear Relationships
Feature Importance
Data Preprocessing
Introduction to Classification
Logistic Regression
Confusion Matrix

Section-4

Support Vector Machine (SVM)

Support Vector Machine (SVM) Concepts
Support Vector Regression

Section-5

Introduction to Decision Tree

Training and Visualizing a Decision Tree
Tree Regression, Regularization and Over Fitting
Matplotlib
Sklearn
Seaborn

Section-6

Ensemble Machine Learning

Ensemble Learning Methods Introduction
Random Forests and Extra-Trees
Project

Section-7

k-Nearest Neighbours

kNN Introduction
Project

Section-8

Unsupervised Learning

Dimensionality Reduction Concept
PCA Introduction
Project

Section-9

Deep Learning

Introduction to Neural Networks
Neural Network Architecture Foundations of Deep Learning Binary Classification Problem Natural Language Processing

FAQ

Why this course is unique?

You get to interact with highly experienced professionals who are AWS certified, have years of real-life projects and training experience. Moreover, Sreeprakash Neelakantan has published a book on Docker!

How is this course conducted, any lab?

This is an instructor-led online course with presentation slides. Each student will be provided access to a cloud-based lab to do all the hands-on exercises.