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Deep Learning
YOLOv6: a single-stage object detection framework dedicated to industrial applications.
Understanding Deep Learning - Simon J.D. Prince
LET-NET: A lightweight CNN network for sparse corners extraction and tracking
Course Repository Machine Learning Essentials Course on Udemy.
Neural Networks: Zero to Hero
You like pytorch? You like micrograd? You love tinygrad! ❤️
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
Machine Learning Q and AI book
Convolutional nets which can take molecular graphs of arbitrary size as input.
CoreNet: A library for training deep neural networks
A PyTorch implementation of Model Agnostic Meta-Learning (MAML) that faithfully reproduces the results from the original paper.
Regularizing Meta-Learning via Gradient Dropout
Minimal and clean examples of machine learning algorithms implementations
Introduction to Machine Learning Systems
A simple and flexible code for Reservoir Computing architectures like Echo State Networks
Paper list about hyperbolic embedding, hyperbolic models,hyperbolic applications
Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
A deep-dive on the entire history of deep-learning
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
Predict operation stocks points (buy-sell) with past technical patterns, and powerful machine-learning libraries such as: Sklearn.RandomForest , Sklearn.GradientBoosting, XGBoost, Google TensorFlow…