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Algorithms Data Science

Stock Prediction Using Deep Learning

Recently have been looking into some stock market prediction libraries and repositories for our group project for CS7643 Deep Learning at Georgia Tech. Previously I worked on traditional Machine Learning algorithms and Q-Learning algorithm from Reinforcement Learning for CS7646: Machine Learning for Trading commonly known as the “ML4T course”. My codes for ML4T is locked […]

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Algorithms Data Science

Resources to Understand Transformer Architecture in NLP

Posting some great resources to understand the Transformer architecture for NLP presented in the paper “Attention is All You Need” (Vaswani et al. 2017). This website by J Al-Ammar is excellent The next best resource is this annotated implementation of Transformer in PyTorch from Harvard University Second, read this article called “Attention! Attention!” by Lilian […]

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Data Science

SQL Notes for Data Science

SQL is one of the most widely used programming language but yet it remains too much undervalued. Here is some quick SQL query snippets for refreshing the memory. Introductory Concepts Optional: Learn about FOREIGN KEY and PRIMARY KEY and the different Database Normalization types from this Wikipedia page. Probably you will need only up to […]

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Data Science OMSCS

Deep Learning Image Processing Tasks

Image Classification: Class distribution per image Semantic Segmentation: Class distribution per pixel Instance Segmentation: Class distribution per pixel with unique ID Object Detection: List of bounding boxes with Class distribution per box

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Data Science

Easy explanation of Convolution vs Cross-Correlation in Convolutional Neural Network (CNN)

Convolution layer for CNN is explained in simple words

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Algorithms Data Science OMSCS

Neural Network Differentiation

To differentiate the loss function in a Neural Network, there are four options Manual differentiation: It is labor intensive and often it is hard to calculate the closed form solution especially for complex function Symbolic differentiation: Like manual, it is also hard for complex function Numerical differentiation: Can handle complex function but may cause numerical […]

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Algorithms Data Science OMSCS

Game Theory Concepts for Reinforcement Learning

There are many flavors of games in Game Theory which are interesting from Machine Learning perspectives, especially from multi-agent Reinforcement Learning applications. Here is the summary of multiple game types are if MinMax algorithm works and what type of strategy one needs to employ.

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Data Science

Information Theory Concepts for Machine Learning

Entropy is the fundamental unit of information in Information Theory and is extensively useful in Machine Learning. Let us introduce the concepts: Entropy, Joint Entropy, Mutual Information.

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Algorithms Data Science

Freelance Machine Learning Project Proposal Template

This is the recommended template for a Project Proposal for a freelance Machine Learning project. This is my personal choice, and definitely depending on project requirements, you might need to explicitly modify change/modify/add to this list. One size does not always fit all for Machine Learning projects. But anyway this could be a good starting point.

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Algorithms Data Science

Policy Iteration, Value Iteration, and Q-Learning

Quick introduction to basic Reinforcement Learning algorithms including Bellman Equation, Policy Iteration, Value Iteration, and Q-Learning