Deep Learning | Tensor Flow | RBM | Auto Encoders | GAN

Deep Learning | Tensor Flow | RBM | Auto Encoders | GAN, available at $49.99, has an average rating of 4.28, with 18 lectures, based on 9 reviews, and has 1052 subscribers.

You will learn about Why we need neural networks? What is a tensor in tensorflow? Math behind neural networks Artificial Neural Network Convolutional Neural Network Recurrent Neural Network Long Short Term Memory This course is ideal for individuals who are Machine Learning Enthusiasts or Students or Machine Learning Engineers It is particularly useful for Machine Learning Enthusiasts or Students or Machine Learning Engineers.

Enroll now: Deep Learning | Tensor Flow | RBM | Auto Encoders | GAN

Summary

Title: Deep Learning | Tensor Flow | RBM | Auto Encoders | GAN

Price: $49.99

Average Rating: 4.28

Number of Lectures: 18

Number of Published Lectures: 18

Number of Curriculum Items: 18

Number of Published Curriculum Objects: 18

Original Price: $59.99

Quality Status: approved

Status: Live

What You Will Learn

Why we need neural networks?
What is a tensor in tensorflow?
Math behind neural networks
Artificial Neural Network
Convolutional Neural Network
Recurrent Neural Network
Long Short Term Memory

Who Should Attend

Machine Learning Enthusiasts
Students
Machine Learning Engineers

Target Audiences

Machine Learning Enthusiasts
Students
Machine Learning Engineers

Deep learning is a rapidly growing field of artificial intelligence that has revolutionized the way we approach and solve complex problems. In this course, we will dive into the fundamentals of deep learning, covering the most important concepts and techniques used in the field.

We will focus on the three major types of deep neural networks

Artificial Neural Networks (ANNs),
Convolutional Neural Networks (CNNs), and
Recurrent Neural Networks (RNNs) and

the three unsupervised deep learning networks like

Boltzmann Machines,
Auto Encoders and
Adversarial Networks.

Using TensorFlow, one of the most popular and widely used deep learning libraries, we will explore the architecture and functioning of each type of network, and learn how to build, train, and evaluate them. From recognizing objects in images to processing sequences of data with higher accuracy, deep learning is finding applications across multiple areas in real-world.

The program covers both concepts as well as coding related to the neural networks.

By the end of this course, you will have a solid understanding of deep learning, and be able to apply these techniques to your own projects. Whether you are a beginner to the field of AI or a seasoned practitioner, this course will equip you with the tools and knowledge you need to advance your skills in deep learning. So, let’s get started on our journey to mastering deep learning!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Tensor Intro

Lecture 1: Tensor Intro

Lecture 2: Tensor Computations

Chapter 3: Understanding Deep Learning

Lecture 1: Understanding Deep Learning in Simple Terms

Lecture 2: Activation Function

Lecture 3: Convex Optimization

Lecture 4: ANN

Chapter 4: Convolution

Lecture 1: Understanding Convolution in CNN

Lecture 2: Deploying a CNN Model

Chapter 5: RNN

Lecture 1: Why RNNs?

Lecture 2: Math Behind RNN

Lecture 3: LSTM

Lecture 4: Spam Detection – RNN & LSTM

Chapter 6: ANN Vs CNN Vs RNN

Lecture 1: ANN Vs CNN Vs RNN

Chapter 7: Unsupervised (Deep) Learning

Lecture 1: Generative Adversarial Network

Lecture 2: Restricted Boltzmann Machines and Deep Belief Networks

Lecture 3: Auto Encoder

Lecture 4: Building The Models

Instructors

SeaportAi .
Artificial Intelligence and Business Transformation Experts

Rating Distribution

1 stars: 1 votes
2 stars: 0 votes
3 stars: 1 votes
4 stars: 1 votes
5 stars: 6 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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