All Projects → Coursework → Similar Projects or Alternatives

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

Pythondemo
虾神的Python示例代码库
Stars: ✭ 221 (-11.24%)
Mutual labels:  jupyter-notebook
Pydqc
python automatic data quality check toolkit
Stars: ✭ 233 (-6.43%)
Mutual labels:  jupyter-notebook
Timeseries fastai
fastai V2 implementation of Timeseries classification papers.
Stars: ✭ 221 (-11.24%)
Mutual labels:  jupyter-notebook
Mozart
An optical music recognition (OMR) system. Converts sheet music to a machine-readable version.
Stars: ✭ 241 (-3.21%)
Mutual labels:  jupyter-notebook
Fauxtograph
Tools for using a variational auto-encoder for latent image encoding and generation.
Stars: ✭ 220 (-11.65%)
Mutual labels:  jupyter-notebook
Web scraping with python
Python 入门爬虫和数据分析实战
Stars: ✭ 234 (-6.02%)
Mutual labels:  jupyter-notebook
Practical 1
Oxford Deep NLP 2017 course - Practical 1: word2vec
Stars: ✭ 220 (-11.65%)
Mutual labels:  jupyter-notebook
Spark Fm Parallelsgd
Implementation of Factorization Machines on Spark using parallel stochastic gradient descent (python and scala)
Stars: ✭ 220 (-11.65%)
Mutual labels:  jupyter-notebook
Socceraction
Convert existing soccer event stream data to SPADL and value player actions
Stars: ✭ 234 (-6.02%)
Mutual labels:  jupyter-notebook
Deform conv pytorch
PyTorch Implementation of Deformable Convolution
Stars: ✭ 217 (-12.85%)
Mutual labels:  jupyter-notebook
Pycon Nlp In 10 Lines
Repository for PyCon 2016 workshop Natural Language Processing in 10 Lines of Code
Stars: ✭ 242 (-2.81%)
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 (-12.45%)
Mutual labels:  jupyter-notebook
My tech resources
List of tech resources future me and other Javascript/Ruby/Python/Elixir/Elm developers might find useful
Stars: ✭ 233 (-6.43%)
Mutual labels:  jupyter-notebook
Hacktoberfest2020
A repo for new open source contributors to begin with open source contribution. Contribute and earn awesome swags.
Stars: ✭ 221 (-11.24%)
Mutual labels:  jupyter-notebook
Bigquery Oreilly Book
Source code accompanying: BigQuery: The Definitive Guide by Lakshmanan & Tigani to be published by O'Reilly Media
Stars: ✭ 246 (-1.2%)
Mutual labels:  jupyter-notebook
Kitti Dataset
Visualising LIDAR data from KITTI dataset.
Stars: ✭ 217 (-12.85%)
Mutual labels:  jupyter-notebook
Pandas Highcharts
Beautiful charting of pandas.DataFrame with Highcharts
Stars: ✭ 233 (-6.43%)
Mutual labels:  jupyter-notebook
Python Awesome
Learn Python, Easy to learn, Awesome
Stars: ✭ 219 (-12.05%)
Mutual labels:  jupyter-notebook
Tacotron pytorch
PyTorch implementation of Tacotron speech synthesis model.
Stars: ✭ 242 (-2.81%)
Mutual labels:  jupyter-notebook
Research Paper Notes
Notes and Summaries on ML-related Research Papers (with optional implementations)
Stars: ✭ 218 (-12.45%)
Mutual labels:  jupyter-notebook
Datasets
source{d} datasets ("big code") for source code analysis and machine learning on source code
Stars: ✭ 231 (-7.23%)
Mutual labels:  jupyter-notebook
Pixel level land classification
Tutorial 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 (-12.85%)
Mutual labels:  jupyter-notebook
Dl tutorial
Tutorials for deep learning
Stars: ✭ 247 (-0.8%)
Mutual labels:  jupyter-notebook
50 Days Of Ml
A day to day plan for this challenge (50 Days of Machine Learning) . Covers both theoretical and practical aspects
Stars: ✭ 218 (-12.45%)
Mutual labels:  jupyter-notebook
Tensorflow 101
TensorFlow Tutorials
Stars: ✭ 2,565 (+930.12%)
Mutual labels:  jupyter-notebook
Medical Ai Course Materials
メディカルAIコース オンライン講義資料
Stars: ✭ 218 (-12.45%)
Mutual labels:  jupyter-notebook
Loss toolbox Pytorch
PyTorch Implementation of Focal Loss and Lovasz-Softmax Loss
Stars: ✭ 240 (-3.61%)
Mutual labels:  jupyter-notebook
Latex ocr
💎 数学公式识别
Stars: ✭ 218 (-12.45%)
Mutual labels:  jupyter-notebook
Relevant Search Book
Code and Examples for Relevant Search
Stars: ✭ 231 (-7.23%)
Mutual labels:  jupyter-notebook
Portrait Shadow Manipulation
Stars: ✭ 217 (-12.85%)
Mutual labels:  jupyter-notebook
Pomegranate
Fast, flexible and easy to use probabilistic modelling in Python.
Stars: ✭ 2,789 (+1020.08%)
Mutual labels:  jupyter-notebook
Paddlehelix
Bio-Computing Platform featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
Stars: ✭ 213 (-14.46%)
Mutual labels:  jupyter-notebook
Mattnet
MAttNet: Modular Attention Network for Referring Expression Comprehension
Stars: ✭ 232 (-6.83%)
Mutual labels:  jupyter-notebook
Malware Detection
Malware Detection and Classification Using Machine Learning
Stars: ✭ 217 (-12.85%)
Mutual labels:  jupyter-notebook
Jetcam
Easy to use Python camera interface for NVIDIA Jetson
Stars: ✭ 242 (-2.81%)
Mutual labels:  jupyter-notebook
Tensorflow
Deep Learning Zero to All - Tensorflow
Stars: ✭ 216 (-13.25%)
Mutual labels:  jupyter-notebook
Statannot
add statistical annotations (pvalue significance) on an existing boxplot generated by seaborn boxplot
Stars: ✭ 228 (-8.43%)
Mutual labels:  jupyter-notebook
Deeplearning
Stars: ✭ 216 (-13.25%)
Mutual labels:  jupyter-notebook
Mixture Density Networks For Distribution And Uncertainty Estimation
A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)
Stars: ✭ 249 (+0%)
Mutual labels:  jupyter-notebook
Text Classification
Text Classification through CNN, RNN & HAN using Keras
Stars: ✭ 216 (-13.25%)
Mutual labels:  jupyter-notebook
Learn Statistical Learning Method
Implementation of Statistical Learning Method, Second Edition.《统计学习方法》第二版,算法实现。
Stars: ✭ 228 (-8.43%)
Mutual labels:  jupyter-notebook
Notebooker
Productionise your Jupyter Notebooks as easily as you wrote them.
Stars: ✭ 215 (-13.65%)
Mutual labels:  jupyter-notebook
Retail Demo Store
AWS Retail Demo Store is a sample retail web application and workshop platform demonstrating how AWS infrastructure and services can be used to build compelling customer experiences for eCommerce, retail, and digital marketing use-cases
Stars: ✭ 238 (-4.42%)
Mutual labels:  jupyter-notebook
Hyperspectral
Deep Learning for Land-cover Classification in Hyperspectral Images.
Stars: ✭ 215 (-13.65%)
Mutual labels:  jupyter-notebook
Introduction To Python
Python is an interpreted, high-level, general-purpose programming language. Created by Guido van Rossum and first released in 1991, Python's design philosophy emphasizes code readability with its notable use of significant white space. (This repository contains Python 3 Code)
Stars: ✭ 232 (-6.83%)
Mutual labels:  jupyter-notebook
Understanding tensorflow nn
🔮Getting started with TensorFlow: Classifying Text with Neural Networks
Stars: ✭ 215 (-13.65%)
Mutual labels:  jupyter-notebook
Jupyter Tips And Tricks
Using Project Jupyter for data science.
Stars: ✭ 245 (-1.61%)
Mutual labels:  jupyter-notebook
Pytorch Superpoint
Superpoint Implemented in PyTorch: https://arxiv.org/abs/1712.07629
Stars: ✭ 214 (-14.06%)
Mutual labels:  jupyter-notebook
Installations mac ubuntu windows
Installations for Data Science. Anaconda, RStudio, Spark, TensorFlow, AWS (Amazon Web Services).
Stars: ✭ 231 (-7.23%)
Mutual labels:  jupyter-notebook
Pytorch Byol
PyTorch implementation of Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning
Stars: ✭ 213 (-14.46%)
Mutual labels:  jupyter-notebook
Deeptextures
Code to synthesise textures using convolutional neural networks as described in Gatys et al. 2015 (http://arxiv.org/abs/1505.07376)
Stars: ✭ 241 (-3.21%)
Mutual labels:  jupyter-notebook
Dagmm
My attempt at reproducing the paper Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection
Stars: ✭ 231 (-7.23%)
Mutual labels:  jupyter-notebook
Mixup Generator
An implementation of "mixup: Beyond Empirical Risk Minimization"
Stars: ✭ 250 (+0.4%)
Mutual labels:  jupyter-notebook
Pytorch modelsize
Estimates the size of a PyTorch model in memory
Stars: ✭ 249 (+0%)
Mutual labels:  jupyter-notebook
Stanford Cs231
Resources for students in the Udacity's Machine Learning Engineer Nanodegree to work through Stanford's Convolutional Neural Networks for Visual Recognition course (CS231n).
Stars: ✭ 249 (+0%)
Mutual labels:  jupyter-notebook
Talks
Stars: ✭ 247 (-0.8%)
Mutual labels:  jupyter-notebook
Audio Classification
Code for YouTube series: Deep Learning for Audio Classification
Stars: ✭ 245 (-1.61%)
Mutual labels:  jupyter-notebook
Mirnet Tfjs
TensorFlow JS models for MIRNet for low-light image enhancement.
Stars: ✭ 145 (-41.77%)
Mutual labels:  jupyter-notebook
Jupyterwith
declarative and reproducible Jupyter environments - powered by Nix
Stars: ✭ 235 (-5.62%)
Mutual labels:  jupyter-notebook
Vae Clustering
Unsupervised clustering with (Gaussian mixture) VAEs
Stars: ✭ 220 (-11.65%)
Mutual labels:  jupyter-notebook
241-300 of 5921 similar projects