minghao2016 Goto Github PK
Name: Ming Hao
Type: User
Bio: Applied Bioinformatics and Chemoinformatics 4 Drug Discovery (ABC4D)
Name: Ming Hao
Type: User
Bio: Applied Bioinformatics and Chemoinformatics 4 Drug Discovery (ABC4D)
Convert trained XGBoost model object in R to SQL script
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
use xgboost and lr model for text classification. xgboost is used to be a feature transform for LR
An R package that makes xgboost models fully interpretable
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.
XLNet: Generalized Autoregressive Pretraining for Language Understanding
An R package to interact with Excel files using the Apache POI java library
Grace (xmgrace) plotting tool
Comfortably converting XML documents to dataframes and vice versa
XML Tools plugin for Notepad++
Xournal++ is a handwriting notetaking software with PDF annotation support. Written in C++ with GTK3, supporting Linux (e.g. Ubuntu, Debian, Arch, SUSE), macOS and Windows 10. Supports pen input from devices such as Wacom Tablets.
xPyder PyMOL Plugin
C++ wrappers for SIMD intrinsics and parallelized, optimized mathematical functions (SSE, AVX, NEON, AVX512)
coming soon
MATLAB toolbox for optimization modeling
An open, extensible Python framework for GPU-accelerated alchemical free energy calculations.
Visual analysis and diagnostic tools to facilitate machine learning model selection.
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models.
Awesome resources of yousan.ai(closely related to deep learning).
A python library for music recommendation
Software to perform shape-based protein structure alignment.
A statistical framework that serves as a common interface to a large range of models
Nextstrain build for Zika virus
Data and scripts for Zika virus tutorial
Nextflow based pipeline for Zika tutorial
Zestimate was created to give consumers as much information as possible about homes and the housing market, marking the first time consumers had access to this type of home value information at no cost. “Zestimates” are estimated home values based on 7.5 million statistical and machine learning models that analyze hundreds of data points on each property. And, by continually improving the median margin of error (from 14% at the onset to 5% today), Zillow has since become established as one of the largest, most trusted marketplaces for real estate information in the U.S. and a leading example of impactful machine learning. Zillow Prize, a competition with a one million dollar grand prize, is challenging the data science community to help push the accuracy of the Zestimate even further. Winning algorithms stand to impact the home values of 110M homes across the U.S. In this million-dollar competition, participants will develop an algorithm that makes predictions about the future sale prices of homes. The contest is structured into two rounds, the qualifying round which opens May 24, 2017 and the private round for the 100 top qualifying teams that opens on Feb 1st, 2018. In the qualifying round, you’ll be building a model to improve the Zestimate residual error. In the final round, you’ll build a home valuation algorithm from the ground up, using external data sources to help engineer new features that give your model an edge over the competition. Because real estate transaction data is public information, there will be a three-month sales tracking period after each competition round closes where your predictions will be evaluated against the actual sale prices of the homes. The final leaderboard won’t be revealed until the close of the sales tracking period.
Platform independent zip compression via miniz
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.