GraphgymPlatform for designing and evaluating Graph Neural Networks (GNN)
Stars: ✭ 344 (-6.01%)
Stock Prediction ModelsGathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
Stars: ✭ 4,660 (+1173.22%)
Mv3dMulti-View 3D Object Detection Network for Autonomous Driving
Stars: ✭ 362 (-1.09%)
ProsprProSPr: Protein Structure Prediction
Stars: ✭ 355 (-3.01%)
Deepstream python appsA project demonstrating use of Python for DeepStream sample apps given as a part of SDK (that are currently in C,C++).
Stars: ✭ 359 (-1.91%)
Predicting PovertyCombining satellite imagery and machine learning to predict poverty
Stars: ✭ 358 (-2.19%)
IvpidPython PID Controller
Stars: ✭ 361 (-1.37%)
Commuter🚎 Notebook sharing hub
Stars: ✭ 353 (-3.55%)
DatascienceA Python library for introductory data science
Stars: ✭ 363 (-0.82%)
Optunityoptimization routines for hyperparameter tuning
Stars: ✭ 362 (-1.09%)
Quantitative NotebooksEducational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
Stars: ✭ 356 (-2.73%)
Tensorflow chessbotPredict chessboard FEN layouts from images using TensorFlow
Stars: ✭ 362 (-1.09%)
Intro programmingA set of IPython notebooks and learning resources for an Introduction to Programming class, focusing on Python.
Stars: ✭ 366 (+0%)
AfinnAFINN sentiment analysis in Python
Stars: ✭ 356 (-2.73%)
GatherSpit shine for Jupyter notebooks 🧽✨
Stars: ✭ 355 (-3.01%)
Lagomlagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.
Stars: ✭ 364 (-0.55%)
Meta RlImplementation of Meta-RL A3C algorithm
Stars: ✭ 355 (-3.01%)
Weakly detectorTensorflow implementation of "Learning Deep Features for Discriminative Localization"
Stars: ✭ 353 (-3.55%)
Workshopslecture notes for cyberwizard workshops
Stars: ✭ 363 (-0.82%)
Machinelearning Deeplearning Nlp Leetcode Statisticallearningmethod Tensorflow最近在学习机器学习,深度学习,自然语言处理,统计学习方法等知识,理论学习主要根据readme的链接,在学习理论的同时,决定自己将学习的相关算法用Python实现一遍,并结合GitHub上相关大牛的代码进行改进,本项目会不断的更新相关算法,欢迎star,fork和关注。 主要包括: 1.吴恩达Andrew Ng老师的机器学习课程作业个人笔记 Python实现, 2.deeplearning.ai(吴恩达老师的深度学习课程笔记及资源) Python实现, 3.李航《统计学习方法》 Python代码实现, 4.自然语言处理NLP 牛津大学xDeepMind Python代码实现, 5.LeetCode刷题,题析,分析心得笔记 Java和Python代码实现, 6.TensorFlow人工智能实践代码笔记 北京大学曹健老师课程和TensorFlow:实战Google深度学习框架(第二版) Python代码实现, 附带一些个人心得和笔记。GitHub上有很多机器学习课程的代码资源,我也准备自己实现一下,后续会更新笔记,代码和百度云网盘链接。 这个项目主要是学习算法的,并且会不断更新相关资源和代码,欢迎关注,star,fork! Min's blog 欢迎访问我的博客主页! (Welcome to my blog website !)https://liweimin1996.github.io/
Stars: ✭ 359 (-1.91%)
Sagemaker DeploymentCode and associated files for the deploying ML models within AWS SageMaker
Stars: ✭ 361 (-1.37%)
QtraderReinforcement Learning for Portfolio Management
Stars: ✭ 363 (-0.82%)
Nerf plNeRF (Neural Radiance Fields) and NeRF in the Wild using pytorch-lightning
Stars: ✭ 362 (-1.09%)
Kaggle titanicthe data and ipython notebook of my attempt to solve the kaggle titanic problem
Stars: ✭ 363 (-0.82%)
SpotmicroaiSpotMicro AI - How to build a self-learning Robot
Stars: ✭ 357 (-2.46%)
Data Science ProjectsDataScience projects for learning : Kaggle challenges, Object Recognition, Parsing, etc.
Stars: ✭ 361 (-1.37%)
Paintschainerline drawing colorization using chainer
Stars: ✭ 3,612 (+886.89%)
Skope Rulesmachine learning with logical rules in Python
Stars: ✭ 362 (-1.09%)
ArticlesA repository for the source code, notebooks, data, files, and other assets used in the data science and machine learning articles on LearnDataSci
Stars: ✭ 350 (-4.37%)
Spec augment🔦 A Pytorch implementation of GoogleBrain's SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
Stars: ✭ 354 (-3.28%)
Tts🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
Stars: ✭ 305 (-16.67%)
Senator FilingsScrape public filings of the buy + sell orders of U.S. senators and calculate their returns
Stars: ✭ 356 (-2.73%)
Pytorch TvmiscTotally Versatile Miscellanea for Pytorch
Stars: ✭ 354 (-3.28%)
Cs229 ml🍟 Stanford CS229: Machine Learning
Stars: ✭ 364 (-0.55%)
Integrated GradientsAttributing predictions made by the Inception network using the Integrated Gradients method
Stars: ✭ 365 (-0.27%)
SdvSynthetic Data Generation for tabular, relational and time series data.
Stars: ✭ 360 (-1.64%)
Deep learning coronavirus cureUsing deep learning to generate novel molecules as candidates for binding with coronavirus protease
Stars: ✭ 361 (-1.37%)