Displaying 1 to 20 from 84 results

LightGBM - A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks

  •    C++

For more details, please refer to Features.Experiments on public datasets show that LightGBM can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. What's more, the experiments show that LightGBM can achieve a linear speed-up by using multiple machines for training in specific settings.

DataflowJavaSDK - Google Cloud Dataflow provides a simple, powerful model for building both batch and streaming parallel data processing pipelines

  •    Java

Google Cloud Dataflow SDK for Java is a distribution of Apache Beam designed to simplify usage of Apache Beam on Google Cloud Dataflow service. This artifact includes the parent POM for other Dataflow SDK artifacts.

Apache Mahout - Scalable machine learning library

  •    Java

Apache Mahout has implementations of a wide range of machine learning and data mining algorithms: clustering, classification, collaborative filtering and frequent pattern mining.

Scikit Learn - Machine Learning in Python

  •    Python

scikit-learn is a Python module for machine learning built on top of SciPy. It is simple and efficient tools for data mining and data analysis. It supports automatic classification, clustering, model selection, pre processing and lot more.

awesome-ml-for-cybersecurity - :octocat: Machine Learning for Cyber Security


A curated list of amazingly awesome tools and resources related to the use of machine learning for cyber security. Please read CONTRIBUTING if you wish to add tools or resources.

gensim - Topic Modelling for Humans

  •    Python

Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community. If this feature list left you scratching your head, you can first read more about the Vector Space Model and unsupervised document analysis on Wikipedia.

textract - extract text from any document. no muss. no fuss.

  •    HTML

Extract text from any document. No muss. No fuss. Full documentation.

python-machine-learning-book - The "Python Machine Learning (1st edition)" book code repository and info resource

  •    Jupyter

This GitHub repository contains the code examples of the 1st Edition of Python Machine Learning book. If you are looking for the code examples of the 2nd Edition, please refer to this repository instead. What you can expect are 400 pages rich in useful material just about everything you need to know to get started with machine learning ... from theory to the actual code that you can directly put into action! This is not yet just another "this is how scikit-learn works" book. I aim to explain all the underlying concepts, tell you everything you need to know in terms of best practices and caveats, and we will put those concepts into action mainly using NumPy, scikit-learn, and Theano.

awesome-datascience - :memo: An awesome Data Science repository to learn and apply for real world problems


An open source Data Science repository to learn and apply towards solving real world problems. First of all, Data Science is one of the hottest topics on the Computer and Internet farmland nowadays. People have gathered data from applications and systems until today and now is the time to analyze them. The next steps are producing suggestions from the data and creating predictions about the future. Here you can find the biggest question for Data Science and hundreds of answers from experts. Our favorite data scientist is Clare Corthell. She is an expert in data-related systems and a hacker, and has been working on a company as a data scientist. Clare's blog. This website helps you to understand the exact way to study as a professional data scientist.

ML-From-Scratch - Machine Learning From Scratch

  •    Python

Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose of this project is not to produce as optimized and computationally efficient algorithms as possible but rather to present the inner workings of them in a transparent and accessible way.

vvedenie-mashinnoe-obuchenie - :memo: Подборка ресурсов по машинному обучению


Постоянно обновляемая подборка ресурсов по машинному обучению. Обсуждение машинного обучения в мессенджерах (группы, каналы, чаты, сообщества).

ferret - Declarative web scraping

  •    Go

ferret is a web scraping system aiming to simplify data extraction from the web for such things like UI testing, machine learning and analytics. Having its own declarative language, ferret abstracts away technical details and complexity of the underlying technologies, helping to focus on the data itself. It's extremely portable, extensible and fast. The following example demonstrates the use of dynamic pages. First of all, we load the main Google Search page, type search criteria into an input box and then click a search button. The click action triggers a redirect, so we wait till its end. Once the page gets loaded, we iterate over all elements in search results and assign the output to a variable. The final for loop filters out empty elements that might be because of inaccurate use of selectors.

MLIB - Apache Spark's scalable machine learning library

  •    Scala

MLlib is a Spark implementation of some common machine learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction and lot more.

InfiniDB - Scale-up analytics database engine for data warehousing and business intelligence

  •    C++

InfiniDB Community Edition is a scale-up, column-oriented database for data warehousing, analytics, business intelligence and read-intensive applications. InfiniDB's data warehouse columnar engine is multi-terabyte capable and accessed via MySQL.

LucidDB - RDBMS built entirely for Data Warehousing and Business Intelligence

  •    Java

LucidDB is the RDBMS built entirely for data warehousing and business intelligence. It is based on architectural cornerstones such as column-store, bitmap indexing, hash join/aggregation, and page-level multi versioning. Every component of LucidDB was designed with the requirements of flexible, high-performance data integration and sophisticated query processing in mind.

Stocktalk - Data collection toolkit for social media analytics

  •    Python

Stocktalk is a visualization tool that tracks tweet volume and sentiment on Twitter, given a series of queries. It does this by opening a local websocket with Twitter and pulling tweets that contain user-specified keywords. For example, I can tell Stocktalk to grab all tweets that mention Ethereum and periodically tally volume and measure average sentiment every 15 minutes.

Knime - Data Analytics Platform

  •    Java

KNIME, pronounced [naim], is a modern data analytics platform that allows you to perform sophisticated statistics and data mining on your data to analyze trends and predict potential results. Its visual workbench combines data access, data transformation, initial investigation, powerful predictive analytics and visualization. KNIME also provides the ability to develop reports based on your information or automate the application of new insight back into production systems.

Orange - Data Mining Suite

  •    Python

Orange is a component-based data mining software. It includes a range of data visualization, exploration, preprocessing and modeling techniques. It supports . interactive data analysis workflows with a large toolbox.