Neural Network Tutorials - Herong's Tutorial Examples
∟References
List of reference materials used in this book.
- Deep Learning, Ian Goodfellow and Yoshua Bengio and Aaron Courville, 2016,
http://www.deeplearningbook.org
- Neural Networks and Deep Learning, Michael Nielsen, 2019,
http://neuralnetworksanddeeplearning.com
- Neural Network Playground, tensorflow.org,
https://playground.tensorflow.org
- Implementing a Neural Network from Scratch, Denny Britz,
https://github.com/dennybritz
- THE MNIST DATABASE of handwritten digits, Yann LeCun,
http://yann.lecun.com/exdb/mnist/
- Make Your Own Neural Network - Python Code Example, Tariq Rashid,
https://github.com/makeyourownneuralnetwork
- Recurrent Neural Networks Tutorial, Denny Britz,
http://www.wildml.com/2015/09/
- Explaining RNNs without neural networks, Terence Parr,
https://explained.ai/rnn/
- Illustrated Guide to LSTM’s and GRU’s: A step by step explanation, Michael Phi,
https://www.michaelphi.com/illustrated-guide-to-lstms-and-grus-a-step-by-step-explanation/
- How To Code Your First LSTM Network In Keras, Ambika Choudhury,
https://analyticsindiamag.com/how-to-code-your-first-lstm-network-in-keras/
- The graph neural network model, Franco Scarselli et al., 2009,
https://persagen.com/files/misc/scarselli2009graph.pdf
- Graphical-Based Learning Environments for Pattern Recognition, Franco Scarselli et al., 2004,
https://link.springer.com/content/pdf/10.1007%2F978-3-540-27868-9_4.pdf
- Graph Neural Network Tensorflow implementation, Matteo Tiezzi,
https://sailab.diism.unisi.it/gnn
- GNN - Python Implementation of Graph Neural Network Model, Matteo Tiezzi and Alberto Rossi,
https://mtiezzi.github.io/gnn_site/
- Generative Adversarial Nets, Ian J. Goodfellow, Jean Pouget-Abadie,
Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozairy, Aaron Courville, Yoshua Bengioz,
https://arxiv.org/pdf/1406.2661.pdf
- Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks,
Alec Radford, et al.,
https://arxiv.org/pdf/1511.06434.pdf
- ENHANCE!: Upscaling images CSI-style with generative adversarial neural networks, Geoffrey Litt,
geoffreylitt.com/2017/06/04/enhance-upscaling-images-with-generative-adversarial-neural-networks.html
- Property Prediction with Neural Networks on Raw Molecular Graphs, Edward Lindelof,
https://github.com/edvardlindelof/
- Understanding and coding Neural Networks From Scratch in Python and R, Sunil Ray, 2020,
https://www.analyticsvidhya.com/blog/2020/07/
- CNNs, An Introduction to Convolutional Neural Networks, Victor Zhou, 2019
https://victorzhou.com/blog/intro-to-cnns-part-1/
- Open Datasets, pathmind.com,
https://pathmind.com/wiki/open-datasets/
- TensorFlow,
https://www.tensorflow.org
- TensorFlow Tutorial For Beginners, Karlijn Willems, 2019,
https://www.datacamp.com/community/tutorials/tensorflow-tutorial
- Getting Started with TensorFlow, Giancarlo Zaccone, 2016,
http://read.pudn.com/downloads779/ebook/3085493/Getting%20Started%20with%20TensorFlow.pdf
- TensorFlow Python API,
https://docs.w3cub.com/tensorflow~python/
- NumPy - Numeric Python, numpy.org,
https://numpy.org
Table of Contents
About This Book
Deep Playground for Classical Neural Networks
Building Neural Networks with Python
Simple Example of Neural Networks
TensorFlow - Machine Learning Platform
PyTorch - Machine Learning Platform
Gradio - ML Demo Platform
CNN (Convolutional Neural Network)
RNN (Recurrent Neural Network)
GNN (Graph Neural Network)
GAN (Generative Adversarial Network)
Performance Evaluation Metrics
►References
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