Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

Python solutions to exercises and tests at http://codility.com/

Temporal Graph Convolutional Network for Urban Traffic Flow Prediction Method

Code & Data for "Tabular Transformers for Modeling Multivariate Time Series" (ICASSP, 2021)

A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.

Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting

Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnot…

Repository for CARTE: Context-Aware Representation of Table Entries

Research on Tabular Foundation Models

Inference code for "TabDPT: Scaling Tabular Foundation Models on Real Data"

⚡ TabPFN: Foundation Model for Tabular Data ⚡

Sequential model-based optimization with a `scipy.optimize` interface

Python package for graph neural networks in chemistry and biology

Automatically extract chemical information from scientific documents

ChemDataExtractor Version 2.0

AI molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design and molecule optimization.

Benchmarks for generative chemistry

Object-oriented refactoring of the YARP package

Automated discovery of reaction Mechanisms and Kinetics

The official sources for the RDKit library

SchNetPack - Deep Neural Networks for Atomistic Systems

A JavaScript Framework for Verifiable Data

Machine learning models to predict the currency exchange rate between given two countries.

Cosmos-Predict1 is a collection of general-purpose world foundation models for Physical AI that can be fine-tuned into customized world models for downstream applications.

GPU accelerated decision optimization

Implementation of Explainable AI (XAI)-driven Interface and a Proof of Concept (POC) Web Application for Financial Transaction Fraud Detection using Machine Learning and Deep Neural Networks.

🚨 Fraud Detection with Deep Neural Networks (PoC) 🤖 A hands-on personal project to predict fraudulent financial transactions using deep learning. Covers the full pipeline: from exploratory data ana…

Credit card fraud detection project that utilizes quantum machine learning techniques

Financial transactions fraud detection using ML (research, experimentation and deployment via Google Cloud)

Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker