Suresh Shanmugam's Projects
Advanced Scikit-learn training session
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
Workshop to demonstrate how to apply NN based algorithms to stock market data and forecast price movements.
Code for "High-Precision Model-Agnostic Explanations" paper
This is an example of a Python Flask app with Elasticsearch/ Elastic App Search with respective Python Clients
📌 Papers, guides, and mentor interviews on applying machine learning for applyingml.com—the ghost knowledge of ML.
Suresh's archive blog on data science
✨ Open-source tool for data-centric NLP. Argilla helps domain experts and data teams to build better NLP datasets in less time.
Your favorite AnchorCMS theme, now for Jekyll!
Lucas' .bashrc file, including git aliases, git alias autocomplete, and git prompt customisation.
Elasticsearch with BERT for advanced document search.
This IPython Notebook contains a quantitative pricing model created for Fast Iron in the Kaggle competition 'Blue Book for Bulldozers'. The model predicts the sale price of a particular piece of heavy equipment so that Fast Iron can create a 'Blue Book' to enable customers to valuate their heavy equipment fleet at auction. Here python is used as a medium to apply supervised and unsupervised machine learning techniques to explain 88.90% of the variance observed in the training set and score an RMSLE of 0.745 when predicting values on the test set. In this competition 590 data scientists created predictive models based on a 'training dataset', provided by Fast Iron, and then used those models to predict sale prices on a 'test set' to compete for a $10,000 dollar award for the team or individual with the most accurate model. The model and methods used for my entry, which scored in the upper 20%, is shown in BlueBook.ipynb.
A Rack application for serving static sites
NYC bike share data exploration
Machine Learning for Crypto Exchanges
Data Science showcase - collection of notebooks with Python & R exploring various topics.
IPython notebooks with analysis
Dionis predictors blender
Notebooks for learning deep learning
A DataMapper adapter for redis
Document Text Recognition (DocTR) made seamless, high-performing & accessible to anyone using Deep Learning for OCR-related tasks.
Collection of workshops to demonstrate best practices in using Amazon EC2 Spot Instances. https://aws.amazon.com/ec2/spot/
Material for re:Invent 2016 - CON314 - Workshop: Deploy a Deep Learning Framework on Amazon ECS and EC2 Spot Instances
Gather data, compute statistics, and make predictions on securities
Example code for the book Fluent Python, 1st Edition (O'Reilly, 2015)
Explains Ruby syntax
🚀 Cookiecutter Template for FastAPI + React Projects. Using PostgreSQL, SQLAlchemy, and Docker
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent