1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

Git Conventional Commits Util to generate Semantic Version and Markdown Change Log and Validate Commit Messag

Educational materials on deep learning by Weights & Biases

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

🔬 Data science environment for k8s

A curated list of software and architecture related design patterns.

Applying UNET Model on TGS Salt Identification Challenge hosted on Kaggle

An emoji guide for your commit messages. 😜

Open Machine Learning Course

Instruct-tune LLaMA on consumer hardware

📧 Epitech Subjects: All the subjects and files related to Epitech PGE Program

🏠 A Data Science Project done to find the factors that most affect the price of an Airbnb listing.

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

⚡ Dynamically generated, customizable SVG that gives the appearance of typing and deleting text for use on your profile page, repositories, or website.

Code for 'The Art of Statistics'

code that makes videos for this: youtube.com/c/primerlearning

This repository will assist you in creating a more beautiful and appealing github profile, and you will have access to a comprehensive range of tools and tutorials for beautifying your github profi…

A Hand Written Digit Recognition app trained on the MNIST dataset of Keras using the CNN model. skills used are Tensorflow, HTML,CSS,javascript.

🎰Handwritten digit recognition application implemented by TensorFlow2 + Keras and Flask.

12 Weeks, 24 Lessons, AI for All!

An easy-to-configure simple resume template built with Flask and Bootstrap.

Streamlit — A faster way to build and share data apps.

A script that trains a model to recognize handwritten digits using the MNIST data set. Then it loads external files and uses the neural network to predict what digits they are.

My Interactive CV built with Python (Dash, Plotly, etc.) and CSS/HTML