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Artificial Neural Networks

curated by Camillo

23 people already started

About this learning path

Artificial Neural Networks

An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.

Artificial Neural Networks comes from the learning path of Machine Learning . Before starting the complex mathematical discussion of neural networks, the implementation is presented. At the end you should be able to differentiate between different archtitectures of neural networks.
The Artificial Neural Networks path can be specialized into Autoencoders & Convolutional Neural Networks & Recurrent Neural Networks & Deep Reinforcement Learning & Generative Adversarial Network .

Web resources
Start immediately and learn at your own pace.

Flexible schedule
Set and adhere to flexible deadlines.

Approx. 3 months to complete
Recommended 12 hours/week

Mostly English

Curator

Camillo Rohe curates
Artificial Neural Networks

This How it Works

You work from module to module. In each module you'll find resources containing:

1. Information

2. Educational content

3. Places to exchange infos

4. Applications, Tools

( 5. Entertaining content )

After studying a resource, you check it.

Learning Path

Module

1

 

DeepLearning.TV Animations

»

Neural Networks and Deep Learning Online Book

»

Deep Learning Fundamentals Online Course

»

Exploring Deep Learning

»

TensorFlow Playground

»

ConvNetJS Web Llibrary

Module

2

»

Backpropagation Algorithm

»

Activation function Method

»

Calculus on Computational Graphs: Backpropagation Article

»

Rectified linear unit (ReLU) Method

»

Intro to Tensorflow for deep learning Online Course

»

Deep Learning Crash Course Series

»

Enterprise Deep Learning with TensorFlow

 

MIT Deep Learning Lecture

Module

3

»

Cross entropy

»

Batch normalization

»

deeplearning.ai Portal

»

Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow

»

Keras Software Library

»

PyTorch Framework

»

TensorFlow Framework

»

Seedbank Database

»

Caffe2 Software-framework

 

Intro to deeplearning Lectures

Module

4

»

deeplearning.net

»

Machine Learning Explained Articles

»

Sebastian Ruder Articles

»

Deep Learning Textbook

»

Neural Networks and Deep Learning Online Course

 

Papers With Code Plattform

 

Lex Fridman Research Scientist