bachaudhry

bachaudhry's Stars

• openai/openai-cookbook

  Examples and guides for using the OpenAI API

  Language:MDX58.4k8684439.3k

• huggingface/diffusers

  🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

  Language:Python25k1934k5.2k

• facebook/prophet

  Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

  Language:Python18.3k4522.1k4.5k

• naklecha/llama3-from-scratch

  llama3 implementation one matrix multiplication at a time

  Language:Jupyter Notebook13k94161k

• SYSTRAN/faster-whisper

  Faster Whisper transcription with CTranslate2

  Language:Python11.3k121673939

• sktime/sktime

  A unified framework for machine learning with time series

  Language:Python7.7k1022.5k1.3k

• alirezadir/Machine-Learning-Interviews

  This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

  Language:Jupyter Notebook4.3k755768

• jdb78/pytorch-forecasting

  Time series forecasting with PyTorch

  Language:Python3.9k41764609

• Nixtla/statsforecast

  Lightning ⚡️ fast forecasting with statistical and econometric models.

  Language:Python3.8k39327267

• karpathy/build-nanogpt

  Video+code lecture on building nanoGPT from scratch

  Language:Python3.4k3419458

• Nixtla/neuralforecast

  Scalable and user friendly neural :brain: forecasting algorithms.

  Language:Python2.9k35526333

• ridgerchu/matmulfreellm

  Implementation for MatMul-free LM.

  Language:Python2.8k4429173

• facebookresearch/Pearl

  A Production-ready Reinforcement Learning AI Agent Library brought by the Applied Reinforcement Learning team at Meta.

  Language:Jupyter Notebook2.6k3157155

• Nixtla/nixtla

  TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

  Language:Jupyter Notebook2.2k36141170

• robjhyndman/forecast

  Forecasting Functions for Time Series and Linear Models

  Language:R1.1k84639341

• JoaquinAmatRodrigo/skforecast

  Time series forecasting with machine learning models

  Language:Python1.1k10166123

• entron/entity-embedding-rossmann

  Language:Jupyter Notebook8703523328

• youssefHosni/Awesome-AI-Data-GitHub-Repos

  A collection of the most important Github repos for ML, AI & Data science practitioners

  652201145

• fastai/diffusion-nbs

  Getting started with diffusion

  Language:Jupyter Notebook6161014275

• fastai/course22p2

  course.fast.ai 2022 part 2

  Language:Jupyter Notebook464229253

• Carl-McBride-Ellis/Compendium-of-free-ML-reading-resources

  Compendium of free ML reading resources

  21611047

• CollinRooney12/htsprophet

  Hierarchical Time Series Forecasting using Prophet

  Language:Python1399639

• google-marketing-solutions/crystalvalue

  Language:Python751417

• youssefHosni/youssefHosni

  647

• carlomazzaferro/scikit-hts-examples

  Example usage of scikit-hts

  Language:Jupyter Notebook5371522

• johnrobinsn/diffusion_experiments

  Language:Jupyter Notebook51224

• fastai/apl-study

  fast.ai APL study group notes

  Language:Jupyter Notebook264618

• ruilin19/DiffEdit-by-Stable-Diffusion

  An unofficial implementation of the paper “DiffEdit: Diffusion-based semantic image editing with mask guidance”

  Language:Python23201

• Willofd101/ziln_cltv

  A python package to train & evaluate Customer Lifetime Value(CLTV) models using Neural Networks & ZILN loss(developed by google)

  Language:Python20232

• daddydrac/customer-lifetime-value-contractual-or-non-contractual-relationship

  Machine Learning to determine Customer Lifetime Value in a contractual or non-contractual setting.

  Language:Jupyter Notebook8004