Intro to Machine Learning and Deep Learning

$79.99

Intro to Machine Learning and Deep Learning

Course
38 Lessons

Artificial Intelligence has taken the world by storm. Machine learning and deep learning are the parts of AI that are responsible for the recent explosion of Generative AI and Large Language Models (LLMs) like ChatGPT. In this course, you will learn about the fundamentals of machine learning and deep learning, understand the types of business problems they solve, and examine how they solve them. The course is based on a workshop delivered by the instructor.

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Section 1: Introduction

This section presents the history and breakdown of machine learning.

Section Description

History of Machine Learning & Deep Learning - Video.mp4

1.1 History of Machine and Deep Learning

1.2 A Breakdown of Machine Learning

Quiz 1

Section 2: Supervised Machine Learning

We explore Supervised Machine Learning, particularly Regression and Classification models.

Section Description

2.1 Regression

2.2 Classification

2.3 Training, Validation, and Testing Data

2.4 Overfitting

Quiz 2

Section 3: Unsupervised and Reinforcement Learning

This short section touches upon the other two branches of Machine learning. The goal is to be able to understand the problem domains where each type of model is applicable.

Section Description

3.1 Clustering

3.2 Dimensionality Reduction

3.3 Reinforcement Learning

Quiz 3

Section 4: Business Use Cases

Understand and correctly identify the business applications of Machine Learning.

Section Description

4.1 Personalized Marketing

4.2 Chatbots

4.3 Catching Fraud

4.4 Customer Segmentation

4.5 Recommender Systems

4.6 Voice Recognition

4.7 Facial Recognition

4.8 Self-Driving Cars

Quiz 4

Section 5: Deep Learning

Deep Learning leverages machine learning models that mimic the learning process in humans and are inspired by the architecture of biological neural networks.

Section Description

5.1 Motivation

5.2 Artificial Neuron

5.3 Inputs and Weights

5.4 Activation Function

5.5 Artificial Neural Networks

5.6 Hidden Layer

5.7 Deep Neural Nets

5.8 A Regression Example

5.9 Building Neural Nets - A Preamble

5.10 Training ANNs - Forward and Back Propagation

Quiz 5