Introduction to Deep Belief Network (DBN) with Python 2023

Introduction to Deep Belief Network (DBN) with Python 2023, available at $54.99, has an average rating of 4.8, with 17 lectures, based on 23 reviews, and has 82 subscribers.

You will learn about Deep Belief Network (DBN) Restricted Boltzmann Machines (RBMs) Contrastive Divergence (CD-k) algorithm Training DBNs Fine-tuning Bayesian Belief Networks (BBNs) This course is ideal for individuals who are Anyone interested in Deep Learning, Machine Learning and Artificial Intelligence or Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence or Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence. or Anyone passionate about Artificial Intelligence or Data Scientists who want to take their AI Skills to the next level It is particularly useful for Anyone interested in Deep Learning, Machine Learning and Artificial Intelligence or Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence or Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence. or Anyone passionate about Artificial Intelligence or Data Scientists who want to take their AI Skills to the next level.

Enroll now: Introduction to Deep Belief Network (DBN) with Python 2023

Summary

Title: Introduction to Deep Belief Network (DBN) with Python 2023

Price: $54.99

Average Rating: 4.8

Number of Lectures: 17

Number of Published Lectures: 17

Number of Curriculum Items: 17

Number of Published Curriculum Objects: 17

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Deep Belief Network (DBN)
Restricted Boltzmann Machines (RBMs)
Contrastive Divergence (CD-k) algorithm
Training DBNs
Fine-tuning
Bayesian Belief Networks (BBNs)

Who Should Attend

Anyone interested in Deep Learning, Machine Learning and Artificial Intelligence
Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence
Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence.
Anyone passionate about Artificial Intelligence
Data Scientists who want to take their AI Skills to the next level

Target Audiences

Anyone interested in Deep Learning, Machine Learning and Artificial Intelligence
Students who have at least high school knowledge in math and who want to start learning Machine Learning, Deep Learning, and Artificial Intelligence
Any data analysts who want to level up in Machine Learning, Deep Learning and Artificial Intelligence.
Anyone passionate about Artificial Intelligence
Data Scientists who want to take their AI Skills to the next level

Interested in Machine Learning, Deep Learning, and Artificial Intelligence? Then this course is for you!

A software engineer has designed this course. With the experience and knowledge I gained throughout the years, I can share my knowledge and help you learn complex theories, algorithms, and coding libraries.

I will walk you into Deep Belief Networks. There are no courses out there that cover Deep Belief networks. However, Deep Belief Networks are used in many applications such as Image recognition, generation, and clustering, Speech recognition, Video sequences, and Motion capture data. So it is essential to learn and understand Deep Belief Network. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

This course is fun and exciting, but at the same time, we dive deep into Deep Belief Networks. Throughout the brand new version of the course, we cover tons of tools and technologies, including:

Google Colab
Deep Belief Network (DBN)
Jupiter Notebook
Artificial Neural Network.
Neuron.
Activation Function.
Keras.
Pandas.
Fine Tuning.
Matplotlib.
Restricted Boltzmann Machines (RBMs)
Contrastive Divergence (CD-k) algorithm
Training DBNs
Bayesian Belief Networks (BBNs)

Moreover, the course is packed with practical exercises based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your models. There are three big projects in this course. These projects are listed below:

MNIST project
Wine project
Movies project.

By the end of the course, you will have a deep understanding of Deep Belief Networks, and you will get a higher chance of getting promoted or a job by knowing Deep belief Networks.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Structure

Lecture 2: IMPORTANT NOTES PLEASE DO NOT SKIP

Lecture 3: Overview of DBNs

Lecture 4: Introduction to BBNs Part 1

Lecture 5: Introduction to BBNs Part 2

Lecture 6: Introduction to RBNs

Lecture 7: Steps to train RBNs

Chapter 2: RBM Recommender System

Lecture 1: Introduction to RBM recommender system, importing libraries and loading dataset

Lecture 2: Normalizing the data

Lecture 3: Gibb's sampling Implementation

Lecture 4: RBM recommender system final implementation and showing the result

Chapter 3: Unsupervised Learning with Deep belief Network

Lecture 1: Unsupervised Learning with Deep belief Network Implementation part 1

Lecture 2: Unsupervised Learning with Deep belief Network Part 2

Lecture 3: Unsupervised Learning with Deep belief Network Final Part

Chapter 4: Supervised Learning with Deep belief Network

Lecture 1: Supervised Learning with Deep Belief Network Implementation Part 1

Lecture 2: Supervised Learning with Deep Belief Network Implementation Part 3

Chapter 5: Thank you

Lecture 1: Thank you

Instructors

Hoang Quy La
Electrical Engineer

Rating Distribution

1 stars: 1 votes
2 stars: 0 votes
3 stars: 3 votes
4 stars: 0 votes
5 stars: 19 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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