Framework and Library for Distributed Online Machine Learning
- machine-learning
- c-plus-plus
- ml
- distributed
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Framework and Library for Distributed Online Machine Learning
Machine Learning toolbox for Humans
Python package for stacking (machine learning technique)
Machine learning for Ruby
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.
A roadmap describing the required skills, learning resources and sample tools to become an AI Engineer
A comprehensive Spark guide collated from multiple sources that can be referred to learn more about Spark or as an interview refresher.
A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.
A simple deep learning library for estimating a set of tags and extracting semantic feature vectors from given illustrations.
The ESP32-S3 bench guide as a React app: live pinout, lessons with interactive simulators, a code reader for the esp-labs firmware, and the bench log. In 11 languages.
A curated collection of free resources to help deepen your understanding of the R programming language. Updated regularly. Contributions encouraged via pull request (see contributing.md).
Simple structured learning framework for python
Reproducing the results of "Playing Atari with Deep Reinforcement Learning" by DeepMind
Remory: Learning Residual Memory for Context Compaction
ZeroCostDL4Mic: A Google Colab based no-cost toolbox to explore Deep-Learning in Microscopy
Common Lisp machine learning library.
oneAPI Data Analytics Library (oneDAL)
A curated list of deep learning resources for video-text retrieval.
🍇 GRAPE is a Rust/Python Graph Representation Learning library for Predictions and Evaluations
Learning from multiple companies in Silicon Valley. Netflix, Facebook, Google, Startups
OmniEdu: Open Foundation Models for Learning and Teaching
Build fully-functioning computer vision models with PyTorch
A series of machine learning tutorials for Torch7
DiffSharp: Differentiable Functional Programming