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deep-learning-and-rare-event-prediction

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Deep Learning and Rare Event Prediction

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# Understanding Deep Learning: Application in Rare Event Prediction

This repository is for the book, [*Understanding Deep Learning: Application in Rare Event Prediction*](https://www.understandingdeeplearning.com).

The link to the book is [here](https://www.understandingdeeplearning.com).

Created and maintained by,

**Chitta Ranjan, Ph.D.**

[mailto](mailto:cran2367@gmail.com): <cran2367@gmail.com>

LinkedIn: [www.linkedin.com/in/chitta-ranjan-b0851911/](https://www.linkedin.com/in/chitta-ranjan-b0851911/)

Medium: [https://medium.com/@cran2367](https://medium.com/@cran2367)

## Chapters

1. Introduction
2. Rare Event Prediction
2. [Setup](/setup-data.ipynb)

a. [Getting Started](/getting-started.ipynb)
    
    b. [Setup data](/setup-data.ipynb)
3. [Multi-layer Perceptron (MLP)](/mlp.ipynb)
4. [Long and Short Term Memory (LSTM)](/lstm.ipynb)
5. [Convolutional Neural Network (CNN)](/cnn.ipynb)
6. Autoencoders

a. [Dense Autoencoders](/dense-autoencoder.ipynb)
	
	b. [LSTM Autoencoders](/lstm-autoencoder.ipynb)
	
	c. [Convolutional Autoencoders](/convolutional-autoencoder.ipynb)
	
	d. [Classifier pretrained with convolutional autoencoder](/classifier-pretrained-with-convolutional-autoencoder.ipynb)
 
8. [Appendix](/utilities)

## Setup Data

1. Download the data from: [data link](https://docs.google.com/forms/d/e/1FAIpQLSdPCkTFW1wTp6tAP1C1BhT7HWTQ60-GfCGvWs9Ca4WbR0FIdg/viewform)
2. Place the data file in the `/data/` directory.

## Video Lectures

The video lectures of the chapter are published on [YouTube](https://www.youtube.com/playlist?list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc).

[Chapter 1-2 - Recap](https://www.youtube.com/watch?v=s8eydoxAIek&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=2&t=743s)

[Chapter 3 - Part 1 - TensorFlow Installation - Background](https://www.youtube.com/watch?v=PDBAWstMFaI&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=2)

[Chapter 3 - Part 2 - Getting Started - TensorFlow on Google Colab](https://www.youtube.com/watch?v=nYdFm0s-k2w&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=3)

[Chapter 3 - Part 3 - Data set for Rare Event Prediction](https://www.youtube.com/watch?v=-rUyr8re9Y0&feature=youtu.be)

[Chapter 4 - Part 1 - Background](https://www.youtube.com/watch?v=56nOUzy8ivM&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=3)

[Chapter 4 - Part 2 - Understanding Multilayer Perceptrons](https://www.youtube.com/watch?v=BSizjaGEcDM&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=4)

[Chapter 4 - Part 3 - Deep Learning and Neural Network](https://www.youtube.com/watch?v=eESFZaePJ6Y&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=5)

[Chapter 4 - Part 4 - Intuition behind Neural Networks](https://www.youtube.com/watch?v=gHG2sJjMv1k&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=6)

[Chapter 4 - Part 5 - MLP Math Operations I](https://www.youtube.com/watch?v=GaR9TfTUupA&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=7)

[Chapter 4 - Part 5 - MLP Math Operations II](https://www.youtube.com/watch?v=zY1q-6k_KVU&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=8)

[Chapter 4 - Part 6 - Importance of Nonlinear Activation](https://www.youtube.com/watch?v=GmHpquoukjM&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=9)

[Chapter 4 - Part 7 - Back Propagation](https://www.youtube.com/watch?v=LOW_KeEAffo&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=10)

[Chapter 4 - Part 8 - Intermission-Outline of rest of the chapter](https://www.youtube.com/watch?v=_Ssk2ISXFSc&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=13&t=0s)

[Chapter 4 - Part 9 - Curve Shifting for Early Prediction](https://www.youtube.com/watch?v=pNUZ1uqDnEY&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=13)

[Chapter 4 - Part 10 - MLP training iteration levels](https://www.youtube.com/watch?v=XNbgcdXSoV8&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=14)

[Chapter 4 - Part 11 - Custom metric in TensorFlow I](https://www.youtube.com/watch?v=txqKQSyeO0M&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=15)

[Chapter 4 - Part 11 - Custom metric in TensorFlow II](https://www.youtube.com/watch?v=yTVWA18kIAM&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=16)

[Chapter 4 - Part 12 - Dropout I - Co-adaptation Phenomenon](https://www.youtube.com/watch?v=0TI8VvSSJjk&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=17)

[Chapter 4 - Part 12 - Dropout II - Underlying Concept](https://www.youtube.com/watch?v=tI02wOXqNE4&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=20&t=0s)

[Chapter 4 - Part 12 - Dropout III (as) A Regularization Technique](https://www.youtube.com/watch?v=xBC0twpyP6s&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=20)

[Chapter 4 - Part 13 - Activations I - Importance of Gradients](https://www.youtube.com/watch?v=5_VMpMOKUOw&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=21)

[Chapter 4 - Part 13 - Activations II -Gradient vis-à-vis Learning](https://www.youtube.com/watch?v=hsBOBcQ2ZUI&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=22)

[Chapter 4 - Part 14 - Vanishing & Exploding Gradient](https://www.youtube.com/watch?v=OlVDuzMUZVI&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=23)

[Chapter 4 - Part 15 - Story of Activation Functions](https://www.youtube.com/watch?v=XuJ6IkkNGeA&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=24)

[Chapter 4 - Part 16 - Rules-of-thumb MLP Dense Layer Models](https://www.youtube.com/watch?v=RE4ZmVA3DTE&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=25)

[Chapter 4 - Codes I - MLP Modeling - Get ready with Data Scaling](https://www.youtube.com/watch?v=1YCpS32_Ym8&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=26)

[Chapter 4 - Codes II - MLP - First (Baseline) Dense Layer Model](https://www.youtube.com/watch?v=FjRIryiAkDk&list=PLlSi-ZIhNrCUcphQRPQt1qEkpUjKsrSSc&index=27)

The videos of the next chapters will be published from now until the end of 2021.

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