ml-mipt VS deepcourse

What are some alternatives?

Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.

open_clip - An open source implementation of CLIP.

MachineLearningWithPython - Get started with Machine Learning with Python - An introduction with Python programming examples

kaggle-courses - Courses on Kaggle

mlops-course - Learn how to design, develop, deploy and iterate on production-grade ML applications.

DeepLearningExamples - State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

pytorch-implementations - A collection of paper implementations using the PyTorch framework

hyperlearn - 2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.

Deep-Learning-Computer-Vision - My assignment solutions for Stanford’s CS231n (CNNs for Visual Recognition) and Michigan’s EECS 498-007/598-005 (Deep Learning for Computer Vision), version 2020.

ml-course - Open Machine Learning course

d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.