ytangukyo's Stars
CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
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 ;)
ludwig-ai/ludwig
Low-code framework for building custom LLMs, neural networks, and other AI models
pymc-devs/pymc
Bayesian Modeling and Probabilistic Programming in Python
aimacode/aima-python
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
cortexlabs/cortex
Production infrastructure for machine learning at scale
GoogleCloudPlatform/training-data-analyst
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
openai/jukebox
Code for the paper "Jukebox: A Generative Model for Music"
pditommaso/awesome-pipeline
A curated list of awesome pipeline toolkits inspired by Awesome Sysadmin
microsoft/vscode-dev-containers
NOTE: Most of the contents of this repository have been migrated to the new devcontainers GitHub org (https://github.com/devcontainers). See https://github.com/devcontainers/template-starter and https://github.com/devcontainers/feature-starter for information on creating your own!
ahkarami/Deep-Learning-in-Production
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
npubird/KnowledgeGraphCourse
东南大学《知识图谱》研究生课程
typedb/typedb
TypeDB: the power of programming, in your database
JohnSnowLabs/spark-nlp
State of the Art Natural Language Processing
higgsfield/RL-Adventure
Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
pymc-devs/pymc-resources
PyMC educational resources
brainflow-dev/brainflow
BrainFlow is a library intended to obtain, parse and analyze EEG, EMG, ECG and other kinds of data from biosensors
handcraftsman/GeneticAlgorithmsWithPython
source code from the book Genetic Algorithms with Python by Clinton Sheppard
AlgoTraders/stock-analysis-engine
Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/
Machine-Learning-Tokyo/papers-with-annotations
Research papers with annotations, illustrations and explanations
BrambleXu/knowledge-graph-learning
A curated list of awesome knowledge graph tutorials, projects and communities.
pymc-devs/pymc4
(Deprecated) Experimental PyMC interface for TensorFlow Probability. Official work on this project has been discontinued.
harvitronix/neural-network-genetic-algorithm
Evolving a neural network with a genetic algorithm.
uber-research/PyTorch-NEAT
aimacode/aima-lisp
Common Lisp implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
jmacglashan/burlap
Repository for the ongoing development of the Brown-UMBC Reinforcement Learning And Planning (BURLAP) java library
dohahelmy/resources-intel-edge-ai-scholarship-2020
A place to collect resources shared bythe community of Intel® Edge AI Foundation course
exercism/common-lisp
Exercism exercises in Common Lisp.
aimlnerd/Deploy-machine-learning-model
Dockerize and deploy machine learning model as REST API using Flask
jmacglashan/burlap_examples
Tutorial and example code for BURLAP (http://burlap.cs.brown.edu)
exercism/prolog
Exercism exercises in Prolog.