Search Results for "q-learning"
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Showing 14 open source projects for "q-learning"
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Top-Rated Free CRM SoftwareHubSpot is an AI-powered customer platform with all the software, integrations, and resources you need to connect your marketing, sales, and customer service. HubSpot's connected platform enables you to grow your business faster by focusing on what matters most: your customers.
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Bright Data - All in One Platform for Proxies and Web ScrapingBright Data offers the highest quality proxies with automated session management, IP rotation, and advanced web unlocking technology. Enjoy reliable, fast performance with easy integration, a user-friendly dashboard, and enterprise-grade scaling. Powered by ethically-sourced residential IPs for seamless web scraping.
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FinMind
Open Data, more than 50 financial data
In the era of big data, data is the foundation of everything. We collect more than 50 kinds of Taiwan stock related information and provide download, online analysis, and backtesting. Regardless of the program, you can download data through the api provided by FinMind, or you can download data directly from the website. After data is available, statistical analysis, regression analysis, time series analysis, machine learning, and deep learning can be performed. For individual stocks, provide... -
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marimo
A reactive notebook for Python
marimo is an open-source reactive notebook for Python, reproducible, git-friendly, executable as a script, and shareable as an app. marimo notebooks are reproducible, extremely interactive, designed for collaboration (git-friendly!), deployable as scripts or apps, and fit for modern Pythonista. Run one cell and marimo reacts by automatically running affected cells, eliminating the error-prone chore of managing the notebook state. marimo's reactive UI elements, like data frame GUIs and plots,... -
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.NET for Apache Spark
A free, open-source, and cross-platform big data analytics framework
.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write... -
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MOA - Massive Online Analysis
Big Data Stream Analytics Framework.
A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. Related to the WEKA project, also written in Java, while scaling to adaptive large scale machine learning. -
The #1 Embedded Analytics Solution for SaaS Teams.Qrvey’s comprehensive embedded analytics software enables you to design more customizable analytics experiences for your end users.
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HPCC Systems
End-to-end big data in a massively scalable supercomputing platform.
HPCC Systems® (www.hpccsystems.com) from LexisNexis® Risk Solutions is a proven, open source solution for Big Data insights that can be implemented by businesses of all sizes. With HPCC Systems, developers can design applications with Big Data at their core, enabling businesses to better analyze and understand data at scale, improving business time to results and decisions. HPCC Systems offers a consistent data-centric programming language, two processing platforms and a single, complete... -
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An introduction to Data Analysis in R
A guide for learning the basic tools on data anaylisis with R
An Introduction to Data Analysis in R [Book] A guide for learning the basic tools on data anaylisis: process, visualize and learn from your data using R programming. This repository holds the necessary data sets for the book "An introduction to Data Analysis in R", to be published by Springer series Use R!. The book can be purchased in XXX. The book is meant as an introductory guide to manipulate data sets in the Big Data paradigm. One of the main goals of this book is to take... -
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Vaex
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python
Data science solutions, insights, dashboards, machine learning, deployment. We start at 100GB. Vaex is a high-performance Python library for lazy Out-of-Core data frames (similar to Pandas), to visualize and explore big tabular datasets. It calculates statistics such as mean, sum, count, standard deviation etc, on an N-dimensional grid for more than a billion (10^9) samples/rows per second. Visualization is done using histograms, density plots and 3d volume rendering, allowing interactive... -
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Neuro
The Neuro crypto currency
The Neuro NRO cryptocurrency is designed to support solutions of machine learning tasks, big data and neural networks. Neuro is a scientific-technical project uniting scientists, engineers and programmers inspired by the idea to build something big, kind and bright. From the first stages of work, we will be engaged in the development of new architectures and algorithms of neural networks. Someday we will undoubtedly enter the annual ImageNet Challenge contest to compete with such giants... -
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Random Bits Forest
RBF: a Strong Classifier/Regressor for Big Data
We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. In conclusion, RBF is a novel framework that performs strongly especially on data... -
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10
Random Bits Regression
Random Bits Regression is a strong general predictor.
... big data analysis but also enables real-time recognition and predictions. The RBR framework also hints the mechanism of brain function and leads to a "wide learning" hypothesis. We believe that this method will make a great impact and enable many downstream applications. -
11
ankus
Data Mining and Machine Learning Algorithms based on MapReduce
[The feature of ankus] * ankus is a 'web-based big data mining project and tool'. - MapReduce-based data mining/machine learning algorithms library - Hadoop-based distributed bigdata system - offering a web-based GUI for easy use [The ankus project & License] * The ankus project consists of three as an open source. * ankus has Dual licensed under the community and commercial licenses. * community license is following GPLv3 - Some algorithms in Core Project do... -
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PROPER is a package for visual evaluation of ranking classifiers for biological big data mining studies in the mathematical language MATLAB. It is an efficient tool for optimization and comparison of the state-of-the-art ranking classifiers by generating over 20 different high quality two- and three-dimensional performance curves.
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13
Chordalysis
Log-linear analysis (data modelling) for high-dimensional data
===== Project moved to https://github.com/fpetitjean/Chordalysis ===== Log-linear analysis is the statistical method used to capture multi-way relationships between variables. However, due to its exponential nature, previous approaches did not allow scale-up to more than a dozen variables. We present here Chordalysis, a log-linear analysis method for big data. Chordalysis exploits recent discoveries in graph theory by representing complex models as compositions of triangular structures,... -
14
iOVFDT
iOVFDT algorithm of incremental decision tree
... incrementally optimized very fast decision tree (iOVFDT). Inheriting the use of Hoeffding bound in VFDT algorithm for node-splitting check, it contains four optional strategies of functional tree leaf, which improve the classifying accuracy. In addition, a multi-objective incremental optimization mechanism investigates a balance among accuracy, mode size and learning speed...
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