All Projects → Materials → Similar Projects or Alternatives

5921 Open source projects that are alternatives of or similar to Materials

Cardio
CardIO is a library for data science research of heart signals
Stars: ✭ 218 (-93.21%)
Mutual labels:  jupyter-notebook
Deeplearning
Some practices about deep learning
Stars: ✭ 210 (-93.46%)
Mutual labels:  jupyter-notebook
Tutorials
AI-related tutorials. Access any of them for free → https://towardsai.net/editorial
Stars: ✭ 204 (-93.65%)
Mutual labels:  jupyter-notebook
Mdrepo
Repositório para armazenamento de código e notebooks de postagens do blog e cursos.
Stars: ✭ 210 (-93.46%)
Mutual labels:  jupyter-notebook
Edaviz
edaviz - Python library for Exploratory Data Analysis and Visualization in Jupyter Notebook or Jupyter Lab
Stars: ✭ 220 (-93.15%)
Mutual labels:  jupyter-notebook
Graph convolutional lstm
Traffic Graph Convolutional Recurrent Neural Network
Stars: ✭ 210 (-93.46%)
Mutual labels:  jupyter-notebook
Rl Adventure 2
PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
Stars: ✭ 2,633 (-18%)
Mutual labels:  jupyter-notebook
Hindi2vec
State-of-the-Art Language Modeling and Text Classification in Hindi Language
Stars: ✭ 211 (-93.43%)
Mutual labels:  jupyter-notebook
Ml Tutorial Experiment
Coding the Machine Learning Tutorial for Learning to Learn
Stars: ✭ 2,489 (-22.49%)
Mutual labels:  jupyter-notebook
Noise2self
A framework for blind denoising with self-supervision.
Stars: ✭ 211 (-93.43%)
Mutual labels:  jupyter-notebook
Tensorface
This repo is deprecated, please use Deep Video Analytics which implements face recognition using TensorFlow and Facenet.
Stars: ✭ 215 (-93.3%)
Mutual labels:  jupyter-notebook
Sttn
[ECCV'2020] STTN: Learning Joint Spatial-Temporal Transformations for Video Inpainting
Stars: ✭ 211 (-93.43%)
Mutual labels:  jupyter-notebook
Stock Prediction
Stock price prediction with recurrent neural network. The data is from the Chinese stock.
Stars: ✭ 219 (-93.18%)
Mutual labels:  jupyter-notebook
Cartoframes
CARTO Python package for data scientists
Stars: ✭ 208 (-93.52%)
Mutual labels:  jupyter-notebook
Python lectures
파이썬Python 강의에 사용되는 소스코드Source Code와 강의 자료들을 모은 repository 입니다.
Stars: ✭ 214 (-93.34%)
Mutual labels:  jupyter-notebook
Image manipulation detection
Paper: CVPR2018, Learning Rich Features for Image Manipulation Detection
Stars: ✭ 210 (-93.46%)
Mutual labels:  jupyter-notebook
Arima Lstm Hybrid Corrcoef Predict
Applied an ARIMA-LSTM hybrid model to predict future price correlation coefficients of two assets
Stars: ✭ 218 (-93.21%)
Mutual labels:  jupyter-notebook
Monthofjulia
Some code examples gathered during my Month of Julia.
Stars: ✭ 209 (-93.49%)
Mutual labels:  jupyter-notebook
Chinese sentiment
中文情感分析,CNN,BI-LSTM,文本分类
Stars: ✭ 216 (-93.27%)
Mutual labels:  jupyter-notebook
Simplified Deeplearning
Simplified implementations of deep learning related works
Stars: ✭ 2,389 (-25.6%)
Mutual labels:  jupyter-notebook
Pytorch Deep Learning Template
A Pytorch Computer Vision template to quick start your next project! 🚀🚀
Stars: ✭ 220 (-93.15%)
Mutual labels:  jupyter-notebook
Book Resources
Stars: ✭ 209 (-93.49%)
Mutual labels:  jupyter-notebook
Epidemiology101
Epidemic Modeling for Everyone
Stars: ✭ 215 (-93.3%)
Mutual labels:  jupyter-notebook
3d Mri Brain Tumor Segmentation Using Autoencoder Regularization
Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).
Stars: ✭ 209 (-93.49%)
Mutual labels:  jupyter-notebook
Tcdf
Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series
Stars: ✭ 217 (-93.24%)
Mutual labels:  jupyter-notebook
Hardware introduction
What scientific programmers must know about CPUs and RAM to write fast code.
Stars: ✭ 209 (-93.49%)
Mutual labels:  jupyter-notebook
Stereo Transformer
Official Repo for Stereo Transformer: Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformers.
Stars: ✭ 211 (-93.43%)
Mutual labels:  jupyter-notebook
Windrose
A Python Matplotlib, Numpy library to manage wind data, draw windrose (also known as a polar rose plot), draw probability density function and fit Weibull distribution
Stars: ✭ 208 (-93.52%)
Mutual labels:  jupyter-notebook
Vae Clustering
Unsupervised clustering with (Gaussian mixture) VAEs
Stars: ✭ 220 (-93.15%)
Mutual labels:  jupyter-notebook
Workshop blog
Stars: ✭ 208 (-93.52%)
Mutual labels:  jupyter-notebook
Gaussianprocesses.jl
A Julia package for Gaussian Processes
Stars: ✭ 214 (-93.34%)
Mutual labels:  jupyter-notebook
Dexplot
Simple plotting library that wraps Matplotlib and integrated with DataFrames
Stars: ✭ 208 (-93.52%)
Mutual labels:  jupyter-notebook
Data Visualization
Data Visualization with Python
Stars: ✭ 217 (-93.24%)
Mutual labels:  jupyter-notebook
Neural differential equations
This is the code for "Neural DIfferential Equations" By Siraj Raval on Youtube
Stars: ✭ 207 (-93.55%)
Mutual labels:  jupyter-notebook
Dianjing
点睛 - 头条号文章标题生成工具 (Dianjing, AI to write Title for Articles)
Stars: ✭ 214 (-93.34%)
Mutual labels:  jupyter-notebook
Flaml
A fast and lightweight AutoML library.
Stars: ✭ 205 (-93.62%)
Mutual labels:  jupyter-notebook
Weightwatcher
The WeightWatcher tool for predicting the accuracy of Deep Neural Networks
Stars: ✭ 213 (-93.37%)
Mutual labels:  jupyter-notebook
Gluon Api
A clear, concise, simple yet powerful and efficient API for deep learning.
Stars: ✭ 2,322 (-27.69%)
Mutual labels:  jupyter-notebook
Bitcoin prediction
This is the code for "Bitcoin Prediction" by Siraj Raval on Youtube
Stars: ✭ 214 (-93.34%)
Mutual labels:  jupyter-notebook
Lstm stock prediction
This is an LSTM stock prediction using Tensorflow with Keras on top.
Stars: ✭ 207 (-93.55%)
Mutual labels:  jupyter-notebook
How To Read Pytorch
Quick, visual, principled introduction to pytorch code through five colab notebooks.
Stars: ✭ 218 (-93.21%)
Mutual labels:  jupyter-notebook
Osumapper
An automatic beatmap generator using Tensorflow / Deep Learning.
Stars: ✭ 207 (-93.55%)
Mutual labels:  jupyter-notebook
Machine Learning Interview Enlightener
This repo is meant to serve as a guide for Machine Learning/AI technical interviews.
Stars: ✭ 207 (-93.55%)
Mutual labels:  jupyter-notebook
Highres Net
Pytorch implementation of HighRes-net, a neural network for multi-frame super-resolution, trained and tested on the European Space Agency’s Kelvin competition.
Stars: ✭ 207 (-93.55%)
Mutual labels:  jupyter-notebook
Mirror
Visualisation tool for CNNs in pytorch
Stars: ✭ 219 (-93.18%)
Mutual labels:  jupyter-notebook
Blazeface Pytorch
The BlazeFace face detector model implemented in PyTorch
Stars: ✭ 203 (-93.68%)
Mutual labels:  jupyter-notebook
Coursera Stanford
Stanford
Stars: ✭ 212 (-93.4%)
Mutual labels:  jupyter-notebook
Instancesegmentation sentinel2
🌱 Deep Learning for Instance Segmentation of Agricultural Fields - Master thesis
Stars: ✭ 206 (-93.58%)
Mutual labels:  jupyter-notebook
Python Sonic
Programming Music with Python, Sonic Pi and Supercollider
Stars: ✭ 217 (-93.24%)
Mutual labels:  jupyter-notebook
Icychesszero
中国象棋alpha zero程序
Stars: ✭ 206 (-93.58%)
Mutual labels:  jupyter-notebook
Skift
scikit-learn wrappers for Python fastText.
Stars: ✭ 213 (-93.37%)
Mutual labels:  jupyter-notebook
Mlapp cn code
《Machine Learning: A Probabilistic Perspective》(Kevin P. Murphy)中文翻译和书中算法的Python实现。
Stars: ✭ 204 (-93.65%)
Mutual labels:  jupyter-notebook
Gwu data mining
Materials for GWU DNSC 6279 and DNSC 6290.
Stars: ✭ 217 (-93.24%)
Mutual labels:  jupyter-notebook
Squad
Building QA system for Stanford Question Answering Dataset
Stars: ✭ 213 (-93.37%)
Mutual labels:  jupyter-notebook
Spark Fm Parallelsgd
Implementation of Factorization Machines on Spark using parallel stochastic gradient descent (python and scala)
Stars: ✭ 220 (-93.15%)
Mutual labels:  jupyter-notebook
Practical 1
Oxford Deep NLP 2017 course - Practical 1: word2vec
Stars: ✭ 220 (-93.15%)
Mutual labels:  jupyter-notebook
Amazing Feature Engineering
Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
Stars: ✭ 218 (-93.21%)
Mutual labels:  jupyter-notebook
Research Paper Notes
Notes and Summaries on ML-related Research Papers (with optional implementations)
Stars: ✭ 218 (-93.21%)
Mutual labels:  jupyter-notebook
Tensorflow
Deep Learning Zero to All - Tensorflow
Stars: ✭ 216 (-93.27%)
Mutual labels:  jupyter-notebook
Statistical Learning Method Solutions Manual
《统计学习方法》(第一版)习题解答,在线阅读地址:https://datawhalechina.github.io/statistical-learning-method-solutions-manual
Stars: ✭ 211 (-93.43%)
Mutual labels:  jupyter-notebook
61-120 of 5921 similar projects