Stars
This repo is meant to serve as a guide for Machine Learning/AI technical interviews.
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023
RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing β¦
Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation
[CVPRW'23 Best Paper Award] Zero-shot Unsupervised Transfer Instance Segmentation
Examples and guides for using the OpenAI API
A playbook for systematically maximizing the performance of deep learning models.
π Guides, papers, lecture, notebooks and resources for prompt engineering
Facestar dataset. High quality audio-visual recordings of human conversational speech.
A self-supervised learning framework for audio-visual speech
Interactive Data Visualization in the browser, from Python
This repo includes ChatGPT prompt curation to use ChatGPT and other LLM tools better.
Port of OpenAI's Whisper model in C/C++
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
π A curated list of awesome resources for product/program managers to learn and grow.
Data science interview questions and answers
π€ Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
A PyTorch-based library for semi-supervised learning (NeurIPS'21)
A C++ standalone library for machine learning
A collection of modern/faster/saner alternatives to common unix commands.
End-to-end ASR/LM implementation with PyTorch
Oboe is a C++ library that makes it easy to build high-performance audio apps on Android.
Flops counter for neural networks in pytorch framework