Understand the concepts and BRANCHES of AI that you'll never find elsewhere!

Understand Machine Learning algorithms STEP-BY-STEP

Be able to implement Machine Learning algorithms in Python

Understand and implement Artificial Neural Network & Deep Learning

Understand and implement Regression, Classification, and Clustering algorithms

Enhance your AI background with Fuzzy Logic and Evolutionary Computation (very USEFUL)

Get a SOLID BACKGROUND in Artificial Intelligence and Machine Learning

Practical exercises step-by-step: handwritten digits recognition, house price prediction, customer segmentation ...

*There are many AI & Machine Learning courses out there BUT most of them teach you how to develop AI applications in just three lines of code! **You will NEVER want that if your objective is to get a solid background in AI from scratch.*

Therefore, this course by Long Nguyen (PhD. AI, France) is aimed at providing you comprehensive fundamentals in AI, from zero to hero! *After completing this course, you will understand and be able to implement the most important methodologies in AI** *such as MACHINE LEARNING, Deep Learning, Fuzzy Logic, and Evolutionary Computation.

Concretely, I will ** walk you step-by-step through the most fundamental AI algorithms** and guide you in many

As having been working very hard and seriously for this project, I really look forward to seeing you in the lectures!

1

Understanding Artificial Intelligence

Welcome to the very first lesson of the "AI & ML course from scratch" by Dr. Long Nguyen!

In this lesson, I will show you some the motivation and the definition of AI as well as some of its examples.

2

QUIZ: Understanding AI

3

Branches of AI

This is a very important lesson!

AI is a very big domain with so many fields that are sometimes confusing. For example today people are talking a lot about AI, Machine Learning, Deep Learning or Reinforcement Learning ... but I know that there are still many people misunderstanding the relationship among these concepts.

By this lesson, you will understand the two different ways to classify AI, and explore its different branches in order to get a correct overview of the domain.

4

QUIZ: Branches of AI

1

What is Machine Learning?

As a matter of fact, Machine Learning may be the most important sub-field of AI today, with so many real-life applications.

So in this lesson, I will introduce to you the motivation and the definitions of Machine Learning.

2

QUIZ: What is Machine Learning

3

Types of Machine Learning

In this lesson, I am going to present to you the three most important types of Machine Learning, they are: Supervised Learning, Unsupervised Learning, and Reinforcement Learning.

4

QUIZ: Types of Machine Learning

1

Setup Jupyter Notebook for Python assignments

1

Linear Regression (part 1)

Linear Regression is a very fundamental tool in Supervised Learning, with so many applications, notably in predictive analysis.

In this lesson, I am going to show you the basic concepts of Linear Regression through a use case.

2

QUIZ: Linear Regression p1

3

Cost function for Linear Regression

4

Linear Regression (part 2)

In this lesson, I will present to you one of the most popular methods to optimize the cost function in Linear Regression, it is called Gradient Descent.

5

QUIZ: Linear Regression p2

6

Gradient descent for Linear Regression

7

Linear Regression (part 3)

In this lesson, you will learn about Multiple Linear Regression, that is, linear regression with more than one variables.

Also, I will give you an interesting point of view about Polynomial Regression.

8

QUIZ: Linear Regression p3

9

Multiple Linear Regression

1

Logistic Regression (part 1)

Logistic Regression is a very basic method for binary classification.

This lesson will show you the concept of decision boundary, which is needed to understand Logistic Regression.

2

QUIZ: Logistic Regression p1

3

Decision boundary

4

Logistic Regression (part 2)

In this lesson, I will show you how we define the sigmoÃ¯de activation function, the cost function, and how to optimize the cost function in Logistic Regression.

5

QUIZ: Logistic Regression p2

6

Cost function for Logistic Regression

7

Logistic Regression (part 3)

In the previous parts, you already learned about Binary classification in which there are only two output classes.

This lesson will present to you the One-versus-All method which is used for Multinomial classification (more than two output classes).

8

QUIZ: Logistic Regression p3

9

Multinomial Classification using One-versus-all method

1

Artificial Neural Network (part 1)

Welcome to the lesson about one of the hottest technology terms today: Artificial Neural Network (ANN)!

In this first part, I am going to present to you the motivation and the definition of ANN, then we will design a simple neuron together.

2

QUIZ: ANN p1

3

Artificial Neural Network (part 2)

In this lesson, I will show you simple and complex Artificial Neural Networks, with a step-by-step calculation example.

Also, you will know what is Deep Learning, a very hot concept today.

4

QUIZ: ANN p2

5

Forward propagation

6

Artificial Neural Network (part 3)

In this lesson, I am going to show you some important notations that we will use through the lesson.

Then, we will discuss about Multinomial classification using Artificial Neural Network, and define the cost function for the problem.

7

QUIZ: ANN p3

8

Artificial Neural Network (part 4)

In this lesson, you will learned about Backpropagation algorithm, a very effective method to calculate partial derivatives of the cost function in Artificial Neural Network, so that we can use Gradient Descent to minimize the cost function in order to find the optimal connection weights.

9

QUIZ: ANN p4

10

Backpropagation

1

Clustering Analysis (part 1)

In this lesson, I will introduce to you the most typical problem in Unsupervised Learning, it is Clustering analysis which has so many important applications in real life.

You will learn about the most basic approach in clustering analysis: the K-means algorithm.

2

QUIZ: Clustering Analysis p1

3

K-means algorithm

4

Clustering Analysis (part 2)

Indeed, running K-means with different random initializations may give different clustering results because K-means algorithm sometimes finds local minima rather than the global minimum. So how do people often do in practice?

Moreover, how can we choose the best number of clusters K?

These questions will be answered in this lesson.

5

QUIZ: Clustering Analysis p2

6

Cost function & Elbow method

1

What is Fuzzy Logic?

Welcome to the world of beautiful logic!

By this lesson, you will find that Fuzzy Logic is very friendly and close to our real life. It is a classical, but a very nice approach in Artificial Intelligence and still has many important applications today.

2

QUIZ: What is Fuzzy Logic

3

Fuzzy Control System (part 1)

Fuzzy control system is a very important aspect in Fuzzy Logic.

Fuzzy control allows us to easily design an intelligent system that can reuse expert's experiences.

In this lesson, you will learn about the three most important stages in a Fuzzy system: Fuzzification, Inferences, and Defuzzification.

4

QUIZ: Fuzzy Control p1

5

Fuzzy Control System (part 2)

This lesson will explain you what is the Inference stage in a Fuzzy control system through intuitive examples.

6

QUIZ: Fuzzy Control p2

7

Fuzzy Control System (part 3)

In this lesson, you will learn about Defuzzification, the last stage in a Fuzzy control system.

8

QUIZ: Fuzzy Control p3

1

What is Evolutionary Computation?

Welcome to a biological class!

In this lesson, you will know how the Biological evolution or the Evolution theory (of Darwin) inspired the creation of a very important branch in AI: Evolutionary Computation.

2

QUIZ: What is Evolutionary Computation

3

Genetic Algorithm (part 1)

This lesson will introduce to you a very famous algorithm in AI: Genetic Algorithm which is inspired by the evolution theory of Darwin.

4

QUIZ: Genetic Algorithm p1

5

Genetic Algorithm (part 2)

In this lesson, we start going into the detail of Genetic Algorithm with chromosome representation, fitness function, and initialization.

6

QUIZ: Genetic Algorithm p2

7

Genetic Algorithm (part 3)

This lesson will show you how we use selection, crossover, and mutation to repeatedly create new generations from the initialized population.

8

QUIZ: Genetic Algorithm p3

1

Thank you!

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