Search Results for "q-learning"
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Showing 87 open source projects for "q-learning"
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New customers get $300 in free credits to spend on Speech-to-Text. All customers get 60 minutes for transcribing and analyzing audio free per month, not charged against your credits.
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The only software you need to increase cash flow, optimize resource utilization, and take control of your assets and inventory.
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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C... -
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Zstandard
Zstandard - Fast real-time compression algorithm
Zstandard is a fast compression algorithm, providing high compression ratios. It also offers a special mode for small data, called dictionary compression. The reference library offers a very wide range of speed / compression trade-off, and is backed by an extremely fast decoder (see benchmarks below). Zstandard library is provided as open source software using a BSD license. Its format is stable and published as IETF RFC 8478. The negative compression levels, specified with --fast=#, offer... -
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GFPGAN
GFPGAN aims at developing Practical Algorithms
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration. Colab Demo for GFPGAN; (Another Colab Demo for the original paper model) Online demo: Huggingface (return only the cropped face) Online demo: Replicate.ai (may need to sign in, return the whole image). Online demo: Baseten.co (backed by GPU, returns the whole image). We provide a clean version of GFPGAN, which can run without CUDA extensions. So that it can run in Windows or on CPU mode. GFPGAN aims at developing... -
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Rubix ML
A high-level machine learning and deep learning library for PHP
Rubix ML is a free open-source machine learning (ML) library that allows you to build programs that learn from your data using the PHP language. We provide tools for the entire machine learning life cycle from ETL to training, cross-validation, and production with over 40 supervised and unsupervised learning algorithms. In addition, we provide tutorials and other educational content to help you get started using ML in your projects. Our intuitive interface is quick to grasp while hiding alot... -
ConnectWise PSA (formerly Manage) allows you to stop working in separate systems, and helps you build a more profitable business. No more duplicate data entries, inefficient employees, manual invoices, and the inability to accurately track client service issues. Get a behind the scenes look into the award-winning PSA that automates processes for each area of business: sales, help desk, support, finance, and HR.
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Hello Algorithm
Animated illustrations, one-click data structure
Animated illustrations, one-click data structure and algorithm tutorials. This project aims to create an open source, free, novice-friendly introductory tutorial on data structures and algorithms. The whole book uses animated illustrations, the content is clear and easy to understand, and the learning curve is smooth, guiding beginners to explore the knowledge map of data structures and algorithms. The source code can be run with one click, helping readers improve their programming skills... -
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FATE
An industrial grade federated learning framework
FATE (Federated AI Technology Enabler) is the world's first industrial grade federated learning open source framework to enable enterprises and institutions to collaborate on data while protecting data security and privacy. It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms... -
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Gym
Toolkit for developing and comparing reinforcement learning algorithms
Gym is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no assumptions about... -
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OpenSpiel
Environments and algorithms for research in general reinforcement
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games. OpenSpiel supports n-player (single- and multi- agent) zero-sum, cooperative and general-sum, one-shot and sequential, strictly turn-taking and simultaneous-move, perfect and imperfect information games, as well as traditional multiagent environments such as (partially- and fully- observable) grid worlds and social dilemmas. OpenSpiel also includes tools... -
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Python Outlier Detection
A Python toolbox for scalable outlier detection
PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural... -
Drive amazing product experiences with quality product data.
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DecisionTree.jl
Julia implementation of Decision Tree (CART) Random Forest algorithm
Julia implementation of Decision Tree (CART) and Random Forest algorithms. -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads: http://arma.sourceforge.net... -
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A rudimentary 3D computer game that utilises artificial neural networks to enable computer agents to anticipate a target's location and shoot (bullets) in the corresponding direction.
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GoDS
Implementation of various data structures and algorithms in Go
GoDS, which means "Go Data Structures", is an implementation of various data structures and algorithms in Go. It provides a wide variety of containers (Sets, Lists, Stacks, Maps, Trees), sets (HashSet, TreeSet, LinkedHashSet), lists (ArrayList, SinglyLinkedList, DoublyLinkedList), stacks (LinkedListStack, ArrayStack), maps (HashMap, TreeMap, HashBidiMap, TreeBidiMap, LinkedHashMap), trees (RedBlackTree, AVLTree, BTree, BinaryHeap), comparators, and iterators. Containers are either ordered or... -
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MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
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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. -
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Bandicoot
fast C++ library for GPU linear algebra & scientific computing
... 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code -
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DuranDuranbot
Teachable/trainable artificially intelligent music bot
A teachable/trainable artificially intelligent music bot fundamentally inspired by how the new wave band Duran Duran composes music. This program utilizes many algorithmic/AI techniques/processes, including machine learning; which allow you to teach/train it to compose music which you prefer... and the technique which is the foundation of the design of DuranDuranbot, which was directly inspired by how Duran Duran writes music........ Called, "bit by bit circular composition"....... and it's... -
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Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll open... -
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code-nav
Professional programming navigation
Programming Navigation is not just a website, but a complete ecology with the goal of "helping everyone discover high-quality programming resources and improve learning efficiency". It contains multiple sub-projects, and the technology stack includes React, Java SpringBoot, Tencent Cloud Development, etc., all of which are open source for everyone to learn, so that you can easily develop beautiful information navigation websites! Most of the programming navigation websites are in disrepair... -
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java-string-similarity
Implementation of various string similarity and distance algorithms
Implementation of various string similarity and distance algorithms: Levenshtein, Jaro-winkler, n-Gram, Q-Gram, Jaccard index, Longest Common Subsequence edit distance, cosine similarity. A library implementing different string similarity and distance measures. A dozen of algorithms (including Levenshtein edit distance and sibblings, Jaro-Winkler, Longest Common Subsequence, cosine similarity etc.) are currently implemented. The main characteristics of each implemented algorithm are presented... -
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PRMLT
Matlab code of machine learning algorithms in book PRML
This Matlab package implements machine learning algorithms described in the great textbook: Pattern Recognition and Machine Learning by C. Bishop (PRML). It is written purely in Matlab language. It is self-contained. There is no external dependency. This package requires Matlab R2016b or latter, since it utilizes a new Matlab syntax called Implicit expansion (a.k.a. broadcasting). It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox... -
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Coach
Enables easy experimentation with state of the art algorithms
... to solve. Coach collects statistics from the training process and supports advanced visualization techniques for debugging the agent being trained. Coach supports many state-of-the-art reinforcement learning algorithms, which are separated into three main classes - value optimization, policy optimization, and imitation learning. Coach supports a large number of environments which can be solved using reinforcement learning. -
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Dopamine
Framework for prototyping of reinforcement learning algorithms
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. It aims to fill the need for a small, easily grokked codebase in which users can freely experiment with wild ideas (speculative research). This first version focuses on supporting the state-of-the-art, single-GPU Rainbow agent (Hessel et al., 2018) applied to Atari 2600 game-playing (Bellemare et al., 2013). Specifically, our Rainbow agent implements the three components identified as most important...