Gluon ApiA clear, concise, simple yet powerful and efficient API for deep learning.
Stars: ✭ 2,322 (+786.26%)
Coursera Deep Learning SpecializationNotes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
Stars: ✭ 188 (-28.24%)
TutorialsAI-related tutorials. Access any of them for free → https://towardsai.net/editorial
Stars: ✭ 204 (-22.14%)
Nn🧑🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Stars: ✭ 5,720 (+2083.21%)
CodesearchnetDatasets, tools, and benchmarks for representation learning of code.
Stars: ✭ 1,378 (+425.95%)
A Nice McCode for "A-NICE-MC: Adversarial Training for MCMC"
Stars: ✭ 115 (-56.11%)
PysotSurrogate Optimization Toolbox for Python
Stars: ✭ 136 (-48.09%)
LacmusLacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.
Stars: ✭ 142 (-45.8%)
ForecastingTime Series Forecasting Best Practices & Examples
Stars: ✭ 2,123 (+710.31%)
Quantum LearningThis repository contains the source code used to produce the results presented in the paper "Machine learning method for state preparation and gate synthesis on photonic quantum computers".
Stars: ✭ 89 (-66.03%)
AdvisorOpen-source implementation of Google Vizier for hyper parameters tuning
Stars: ✭ 1,359 (+418.7%)
YaboxYet another black-box optimization library for Python
Stars: ✭ 103 (-60.69%)
Sigmoidal aiTutoriais de Python, Data Science, Machine Learning e Deep Learning - Sigmoidal
Stars: ✭ 103 (-60.69%)
Optimization PythonGeneral optimization (LP, MIP, QP, continuous and discrete optimization etc.) using Python
Stars: ✭ 133 (-49.24%)
Deep Learning With PythonExample projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.
Stars: ✭ 134 (-48.85%)
Python autocompleteUse Transformers and LSTMs to learn Python source code
Stars: ✭ 123 (-53.05%)
Dive Into Dl Pytorch本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
Stars: ✭ 14,234 (+5332.82%)
IminuitJupyter-friendly Python interface for C++ MINUIT2
Stars: ✭ 172 (-34.35%)
AttentionnAll about attention in neural networks. Soft attention, attention maps, local and global attention and multi-head attention.
Stars: ✭ 175 (-33.21%)
Deep Learning NotesMy personal notes, presentations, and notebooks on everything Deep Learning.
Stars: ✭ 191 (-27.1%)
RadioRadIO is a library for data science research of computed tomography imaging
Stars: ✭ 198 (-24.43%)
Training MaterialA collection of code examples as well as presentations for training purposes
Stars: ✭ 85 (-67.56%)
Neural TangentsFast and Easy Infinite Neural Networks in Python
Stars: ✭ 1,357 (+417.94%)
Knet.jlKoç University deep learning framework.
Stars: ✭ 1,260 (+380.92%)
PytorchnlpbookCode and data accompanying Natural Language Processing with PyTorch published by O'Reilly Media https://nlproc.info
Stars: ✭ 1,390 (+430.53%)
Neural Networksbrief introduction to Python for neural networks
Stars: ✭ 82 (-68.7%)
Hep mlMachine Learning for High Energy Physics.
Stars: ✭ 133 (-49.24%)
Pytorch Model ZooA collection of deep learning models implemented in PyTorch
Stars: ✭ 125 (-52.29%)
Pytorch 101 Tutorial SeriesPyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.
Stars: ✭ 136 (-48.09%)
AutoencodersImplementation of simple autoencoders networks with Keras
Stars: ✭ 123 (-53.05%)
Fantasy Basketball Scraping statistics, predicting NBA player performance with neural networks and boosting algorithms, and optimising lineups for Draft Kings with genetic algorithm. Capstone Project for Machine Learning Engineer Nanodegree by Udacity.
Stars: ✭ 146 (-44.27%)
100daysofmlcodeMy journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.
Stars: ✭ 146 (-44.27%)
Ml Workspace🛠 All-in-one web-based IDE specialized for machine learning and data science.
Stars: ✭ 2,337 (+791.98%)
Hyperlearn50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster
Stars: ✭ 1,204 (+359.54%)
Shape Detection🟣 Object detection of abstract shapes with neural networks
Stars: ✭ 170 (-35.11%)
Deep Math Machine Learning.aiA blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.
Stars: ✭ 173 (-33.97%)
FixyAmacımız Türkçe NLP literatüründeki birçok farklı sorunu bir arada çözebilen, eşsiz yaklaşımlar öne süren ve literatürdeki çalışmaların eksiklerini gideren open source bir yazım destekleyicisi/denetleyicisi oluşturmak. Kullanıcıların yazdıkları metinlerdeki yazım yanlışlarını derin öğrenme yaklaşımıyla çözüp aynı zamanda metinlerde anlamsal analizi de gerçekleştirerek bu bağlamda ortaya çıkan yanlışları da fark edip düzeltebilmek.
Stars: ✭ 165 (-37.02%)
Quant NotesQuantitative Interview Preparation Guide, updated version here ==>
Stars: ✭ 180 (-31.3%)
Far HoGradient based hyperparameter optimization & meta-learning package for TensorFlow
Stars: ✭ 161 (-38.55%)
TcdfTemporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series
Stars: ✭ 217 (-17.18%)
Pixel level land classificationTutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.
Stars: ✭ 217 (-17.18%)
MydatascienceportfolioApplying Data Science and Machine Learning to Solve Real World Business Problems
Stars: ✭ 227 (-13.36%)
Neural Network From ScratchEver wondered how to code your Neural Network using NumPy, with no frameworks involved?
Stars: ✭ 230 (-12.21%)
Mit Deep LearningTutorials, assignments, and competitions for MIT Deep Learning related courses.
Stars: ✭ 8,912 (+3301.53%)
Math And Ml NotesBooks, papers and links to latest research in ML/AI
Stars: ✭ 76 (-70.99%)
Bayesian OptimizationPython code for bayesian optimization using Gaussian processes
Stars: ✭ 245 (-6.49%)