6794 Open source projects that are alternatives of or similar to Pancancer

Software analytics tool that helps developers analyse and improve software quality.

Machine learning for Project Cognoma

Machine learning to classify Malicious (Spam)/Benign URL's

Osintgram is a OSINT tool on Instagram. It offers an interactive shell to perform analysis on Instagram account of any users by its nickname

This repository contains three ways to obtain arbitrage which are Dual Listing, Options and Statistical Arbitrage. These are projects in collaboration with Optiver and have been peer-reviewed by staff members of Optiver.

Extracting biomedical relationships from literature with Snorkel 🏊

Object classification with CIFAR-10 using transfer learning

Udacity Self-Driving Car Engineer Nanodegree. Project: Vehicle Detection and Tracking

Shared Latent Space VAE's

Training and evaluating a variational autoencoder for pan-cancer gene expression data

Repository for the paper "Automated Hate Speech Detection and the Problem of Offensive Language", ICWSM 2017

An unsupervised transfer learning approach for rare disease transcriptomics

🍝 Pastas is an open-source Python framework for the analysis of hydrological time series.

python implementations of Analyzing Neural Time Series Textbook

Stock Price Prediction using Machine Learning Techniques

🚀 A statistical analysis tool for performance testing

Denoising Autoencoders for Phenotype Stratification

Python toolbox / library for power system transient dynamics simulation with symbolic modeling and numerical analysis 🔥

生命情報の機械学習入門（新学術領域「先進ゲノム支援」中級講習会資料）

Numerical simulations using flexible Lattice Boltzmann solvers

Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs, ICML 2019

1.Android的短信通过邮件或者钉钉转出去 APP下载[http://tsms.allmything.com/topic/3] 讨论社区 [http://tsms.allmything.com]

LiQi of robinwen.

Série histórica dos dados sobre COVID-19, a partir de informações do Ministério da Saúde

Deep Learning: Image classification, feature visualization and transfer learning with Keras

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

Machine learning projects, often on audio datasets

Amazon SageMaker examples for prebuilt framework mode containers, a.k.a. Script Mode, and more (BYO containers and models etc.)

scaffold of Apache Airflow executing Docker containers

Resources for Machine Learning Pocket Reference

Machine learning portfolio

Tianchi medical AI competition [Season 1]: Lung nodules image segmentation of U-Net. U-Net训练基于卷积神经网络的肺结节分割器

Colorise Anime/Manga Sketches with DeOldify

statistics and classes for exploratory spatial data analysis

Python codes for low-rank tensor factorization, tensor completion, and tensor regression techniques.

CallMon is an experimental system call monitoring tool that works on Windows 10 versions 2004+ using PsAltSystemCallHandlers

Compressed Sensing MRI based on Deep Generative Adversarial Network

Solution of RecSys Challenge 2015

Local AI demo and distributed AI demo using TensorFlow

A short tutorial for Torchtext, the NLP-specific add-on for Pytorch.

brief introduction to Python for neural networks

📚 Control Functions For Single-Board Computers

CAUTION: This is not maintained anymore. Visit https://github.com/chainer-community/chainer-colab-notebook/

simple rules engine

Inference case studies in jupyter

Neural machine translator for English2German translation.

My repository for the Carvana Image Masking Challenge

A Notebook where I implement differents anomaly detection algorithms on a simple exemple. The goal was just to understand how the different algorithms works and their differents caracteristics.

Powerful, automated analysis and design of quantum microwave chips & devices [Energy-Participation Ratio and more]

Software for the visualization of sequence-function relationships

A command-line validation tool for AWS Cloud Formation that allows to conquer the cloud faster!

Keras implementation of NASNet-A

It is the DKT+ model implemented in python3 and tensorflow1.2

Deobfuscation and analysis of PHP malware captured by a WordPress honey pot

Papers I read