Deep Learning for Beginners

This paper summarizes resources for deep learning for beginners.

Overview

First CNN Example

MNIST dataset is probably the most popular for create the first CNN example. It consists of 70,000 images of handwritten digits from 0-9.

Depending on your preference of the programming languages, there are Python and Matlab examples available.

• Python: Building a Convolutional Neural Network (CNN) in Keras. If you are using Python, you need to properly install software and configure your environments.
• Matlab: Create Simple Deep Learning Network for Classification. The Matlab Deep Learning Toolbox needs to be installed before you run the example.

Convolutional Neural Networks (CNN)

What is Convolutional Neural Networks (CNN)

• A Comprehensive Guide to Convolutional Neural Networks
• Matlab, Explanation of Different Layers of Convolutional Neural Networks

CNN Examples

• Your First Deep Learning Project in Python with Keras Step-By-Step
• How to Develop 1D Convolutional Neural Network Models for Human Activity Recognition

Common CNN Architecture

• Illustrated: 10 CNN Architectures: LeNet-5, AlexNet, VGG-16, Inception-v1, Inception-v3, ResNet-50, Xception, Inception-v4, Inception-ResNets, ResNeXt-50

AlexNet

• Understanding AlexNet
• Implementing AlexNet CNN Architecture Using TensorFlow 2.0+ and Keras

Few Shot Learning

• An Introduction to Few-Shot Learning
• Understanding Few-Shot Learning in Computer Vision – What You Need to Know

Development Tool

Python

• Anaconda Distribution

Keras

• Getting started with the Keras Sequential model
• Simple MNIST convnet
• Keras Code examples

Matlab

• Matlab, Convolutional Neural Networks
• Matlab, Training a Model from Scratch

Code Snippet

• Check the installed packages

  conda list
  

• Install a particular tensorflow version using conda

  conda install -c conda-forge tensorflow=1.13
  

Deep Learning Tutorials

• How to Configure the Learning Rate When Training Deep Learning Neural Networks

Online Resources

• CS231n: Convolutional Neural Networks for Visual Recognition at Stanford University link
• A summary of resources link
• Book Dive into Deep Learning

Matlab Resources

Matlab has provided lots of useful resources.

• Set Up Parameters and Train Convolutional Neural Network
• Deep Learning Tips and Tricks
• Data Sets for Deep Learning
• Matlab, Explanation of Different Layers of Convolutional Neural Networks