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12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Python programs, usually short, of considerable difficulty, to perfect particular skills.
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
A High-Quality Real Time Upscaler for Anime Video
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…
A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: 🇺🇸 🇨🇳 🇯🇵 🇮🇹 🇰🇷 🇷🇺 🇧🇷 🇪🇸
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Your new Mentor for Data Science E-Learning.
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
Best Practices, code samples, and documentation for Computer Vision.
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
A collection of pre-trained, state-of-the-art models in the ONNX format
A scikit-learn compatible neural network library that wraps PyTorch
Tacotron 2 - PyTorch implementation with faster-than-realtime inference
Reference models and tools for Cloud TPUs.
Code repo for realtime multi-person pose estimation in CVPR'17 (Oral)
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse m…
Efficient neural feature detector and descriptor
Keras Implementation of Neural Style Transfer from the paper "A Neural Algorithm of Artistic Style" (http://arxiv.org/abs/1508.06576) in Keras 2.0+
subpixel: A subpixel convnet for super resolution with Tensorflow
DL course co-developed by YSDA, HSE and Skoltech