6217 Open source projects that are alternatives of or similar to Corus

Performance analysis of predictive (alpha) stock factors

Programs for stock prediction and evaluation

PennAI: AI-Driven Data Science

2018达观杯长文本分类智能处理挑战赛 18解决方案

PyTorch Implementation of Realtime Multi-Person Pose Estimation project.

A numpy implementation of forward energy from the paper “Improved Seam Carving for Video Retargeting" (2008)

Unofficial Implementation of RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series (AAAI 2019)

Python solutions to the problem sets of Stanford's graduate course on Machine Learning, taught by Prof. Andrew Ng

Shifting More Attention to Video Salient Objection Detection, CVPR 2019 (Best paper finalist & Oral)

2nd Place Solution 💰🥈

Second edition of Springer Book Python for Probability, Statistics, and Machine Learning

Repo replaced by cogsec-collaborative/AMITT

Statistical Rethinking (2nd Ed) with Tensorflow Probability

PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks

开源的各大比赛baseline

Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

Python tutorials and puzzles to share with the world!

This repo contains my coursework, assignments, and Slides for Natural Language Processing Specialization by deeplearning.ai on Coursera

nbconvert as a web service: Render Jupyter Notebooks as static web pages

Implemention of FCN-8 and FCN-16 with Keras and uses CRF as post processing

📈 如何用深度强化学习自动炒股

Course materials for teaching data visualization in Python.

A minimal implementaion (less than 150 lines of code with visualization) of DCGAN/WGAN in PyTorch with jupyter notebooks

Keras Implementation of Neural Style Transfer from the paper "A Neural Algorithm of Artistic Style" (http://arxiv.org/abs/1508.06576) in Keras 2.0+

Introduction to Statistical Modeling with Python (PyCon 2017)

Repo that contains the supporting material for O'Reilly Webinar "An Intro to Predictive Modeling for Customer Lifetime Value" on Feb 28, 2017

Pytorch Implementation of Perceptual Losses for Real-Time Style Transfer and Super-Resolution

DataGene - Identify How Similar TS Datasets Are to One Another (by @firmai)

Chapterwise code available in the book

Tools and Docs on the Azure Data Science Virtual Machine (http://aka.ms/dsvm)

Repositório do Deep Learning Book - www.deeplearningbook.com.br

Jupyter notebook server extension to proxy web services.

I used Machine Learning to make a Logistic Regression model using scikit-learn, pandas, numpy, seaborn and matplotlib to predict the results of FIFA 2018 World Cup.

Almost Real-time Object Detection using Apple's CoreML and YOLO v1 -

SphereFace+ Implementation for <Learning towards Minimum Hyperspherical Energy> in NIPS'18.

Multiscale Geographically Weighted Regression (MGWR)

Fundamentals of Spark with Python (using PySpark), code examples

(한국어) 텍스트 마이닝을 위한 공부거리들

Projects done in the Data Engineering Nanodegree by Udacity.com

Label line using matplotlib.

Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron

Predict remaining useful life of a component based on historical sensor observations using automated feature engineering

Powerful financial charting library based on R's Quantmod | http://py-quantmod.readthedocs.io/en/latest/

Fast Depth Densification for Occlusion-Aware Augmented Reality

Multi dimensional LSTM as described in Alex Graves' Paper https://arxiv.org/pdf/0705.2011.pdf

Main code for Parcels (Probably A Really Computationally Efficient Lagrangian Simulator)

This is the code for "Sentiment Analysis - Data Lit #1" by Siraj Raval on Youtube

Stereo convolutional neural network for depth map prediction from stereo images

This repository contains the Tutorials for the NPTEL MOOC on Machine Learning.

What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.

Implementations of some popular Saliency Maps in Keras

This repository contains code for the paper Learning by Association - A versatile semi-supervised training method for neural networks (CVPR 2017) and the follow-up work Associative Domain Adaptation (ICCV 2017).

Modification of fast.ai deep learning course notebooks for usage with Keras 2 and Python 3.

Example for end-to-end machine learning on Kubernetes using Kubeflow and Seldon Core