Deep Learning: Neural Networks from scratch using Javascript

Deep Learning: Neural Networks from scratch using Javascript, available at Free, has an average rating of 4.35, with 8 lectures, based on 32 reviews, and has 4284 subscribers.

You will learn about How to implement a Artificial Deep Neural Network from scratch How back-propagation algorithm works How to train an Artificial Deep Leaning model in the browser using Javascript Convolutional Neural Network Architectures How to build a handwritten digit recogniser model This course is ideal for individuals who are Web developers curious about deep learning and AI It is particularly useful for Web developers curious about deep learning and AI.

Enroll now: Deep Learning: Neural Networks from scratch using Javascript

Summary

Title: Deep Learning: Neural Networks from scratch using Javascript

Price: Free

Average Rating: 4.35

Number of Lectures: 8

Number of Published Lectures: 8

Number of Curriculum Items: 8

Number of Published Curriculum Objects: 8

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

How to implement a Artificial Deep Neural Network from scratch
How back-propagation algorithm works
How to train an Artificial Deep Leaning model in the browser using Javascript
Convolutional Neural Network Architectures
How to build a handwritten digit recogniser model

Who Should Attend

Web developers curious about deep learning and AI

Target Audiences

Web developers curious about deep learning and AI

This course will teach how to build and train an Artificial Neural Network from scratch using only Javascript(No library). We will use only an IDEA and a browser.

It is structured to help you genuinely learn Deep Learning by starting from the basics until advanced concepts. We will learn and code every component of a Deep learning architecture from scratch, uncovering all the magic behind Artificial Neural Networks.

To prepare the students for real life, we will develop our ANN framework following the TensorFlow API, and we will compare our implementation with Tensorflow.js, this way you will know what is under the hood of the Deep learning libraries.

In this course, we will create a handwritten digit recognizer model using three different model approaches:

Fully Connected Neural Network – Vanilla Artificial Neural Network
Fully Connected Neural Network (also known as a DenseNet) Using TensorFlow.js
Convolutional Neural Network(also known as a ConvNet or CNN) Using TensorFlow.js

Deep learning is a field of study traditionally reserved for researchers or engineers with advanced degrees, and because of that, many developers feel very intimidated to learn this technology. However, when you start learning the mystery behind the “magic”, you will realize that there is no reason to be intimidated. And that’s why I decided to create this course.

By following this course until the end, you will get insights and feel empowered to dive deep into the Deep Learning field to improve the experience of your projects.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Feedback

Lecture 3: Source code

Lecture 4: Preparing the dataset

Lecture 5: Model architecture

Lecture 6: Model training

Lecture 7: Activation function

Lecture 8: Model evaluation

Instructors

Alexsandro Souza
Tech Lead

Rating Distribution

1 stars: 1 votes
2 stars: 1 votes
3 stars: 1 votes
4 stars: 10 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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