data-science

Explore my diverse collection of projects showcasing machine learning, data analysis, and more. Organized by project, each directory contains code, datasets, documentation, and resources. Dive in, to discover insights and techniques in data science. Reach out for collaborations and feedback.

Yet another redundant workflow engine

NLP Zero to Hero in just 10 Kernels

Fast Disk-Based Parallelized Data Manipulation Framework for Larger-than-RAM Data

Unified MySQL, Postgres & FlightSQL Server, Powered by DuckDB.

Data Package is a standard consisting of a set of simple yet extensible specifications to describe datasets, data files and tabular data. It is a data definition language (DDL) and data API that facilitates findability, accessibility, interoperability, and reusability (FAIR) of data.

Modeltime unlocks time series forecast models and machine learning in one framework

Official Repo for the Efficient Python for Data Scientists Book. You can buy the book from here:

A high-performance, arbitrary-precision, floating-point decimal library.

A simplified framework and utilities for PyTorch

A curated list of data science educational resources for essential data science skills

Obsidian tools - a Python package for analysing an Obsidian.md vault

:octocat:🌟 The Ultimate resources for beginner to advanced level projects all in one place 💻 🎯🚀

DataCamp Project Solutions

A unified interface for optimization algorithms and experiments

A curated list of artificial intelligence resources (Courses, Tools, App, Open Source Project)

This repository contains a reading list of papers on Time Series Segmentation. This repository is still being continuously improved.

Automate Data Exploration and Treatment

Your no-nonsense guide to the Math used in Artificial Intelligence

A simple & elegant experiment tracking framework that integrates persistence logic & best practices directly into Python

Distributed Machine Learning Patterns from Manning Publications by Yuan Tang https://bit.ly/2RKv8Zo

apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly. See the documentation page: https://apricot-select.readthedocs.io/en/latest/index.html

A collection of data science and machine learning resources that I've found helpful (I only post what I've read!)

Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

Data Science in Julia course for JuliaAcademy.com, taught by Huda Nassar

Human-explainable AI.

Curated list of known efforts in materials informatics, i.e. in modern materials science

Visualise your CSV files in seconds without sending your data anywhere

Source for Who're Interested in Data!

Easy to use Python library of customized functions for cleaning and analyzing data.