Search Results for "q learning algorithm"
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20 projects for "q learning algorithm" with 2 filters applied:
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JavaScript Algo and Data Structures
Algorithms and data structures implemented in JavaScript
javascript-algorithms is an open source repository by Oleksii Trekhleb that provides implementations of algorithms and data structures in JavaScript. Each algorithm includes explanations, complexity analysis, and references for further reading, making it both a coding resource and a study guide. The repository covers topics such as sorting, searching, graph algorithms, cryptography, and data structures like linked lists, stacks, and queues. It is designed to help developers understand... -
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CodeGuide
This repository is a collection of the author, Xiao Fuge
CodeGuide is a curated collection of Java development resources built from years of real-world engineering experience by the author, who has worked extensively in large-scale internet companies. The project serves as a structured and comprehensive learning path for developers who want to strengthen their understanding of Java fundamentals and core programming practices. It includes detailed explanations of design patterns, source code analysis, frameworks, algorithms, and real-world project... -
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TorchQuantum
A PyTorch-based framework for Quantum Classical Simulation
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers. Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing. -
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[OFFICIAL] tinyfiledialogs C C++ v3.21.2
inputbox password WIN OSX GTK QT Console VCPKG C# Lua R Fortran Pascal
one C/C++ file & header ==> 8 functions: - beep - tray notify popup - message & question - input & password - save file - open file(s) - select folder - color picker complements OpenGL Vulkan GLFW GLUT GLUI VTK SFML TGUI SDL Ogre Unity3d ION OpenCV CeGui MathGL GLM CPW GLOW Open3D ImGui MyGui GLT NGL STB Nuklear Fenster MicroUi & head-less programs NO INIT NO MAIN LOOP NO LINKING NO INCLUDE win (XP to 11) ASCII MBCS UTF-8 UTF-16 (wchar_t) - native dialogs osx/unix... -
Cloud data warehouse to power your data-driven innovationBigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
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Supervised Reptile
Code for the paper "On First-Order Meta-Learning Algorithms"
The supervised-reptile repository contains code associated with the paper “On First-Order Meta-Learning Algorithms”, which introduces Reptile, a meta-learning algorithm for learning model parameter initializations that adapt quickly to new tasks. The implementation here is aimed at supervised few-shot learning settings (e.g. Omniglot, Mini-ImageNet), not reinforcement learning, and includes scripts to run training and evaluation for few-shot classification. ... -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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benchm-ml
A benchmark of commonly used open source implementations
...The benchmarks cover algorithms like logistic regression, random forest, gradient boosting, and deep neural networks, and they compare across toolkits such as scikit-learn, R packages, xgboost, H2O, Spark MLlib, etc. The repository is structured in logical folders, each corresponding to algorithm categories. -
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OpenDino
Open Source Java platform for Optimization, DoE, and Learning.
OpenDino is an open source Java platform for optimization, design of experiment and learning. It provides a graphical user interface (GUI) and a platform which simplifies integration of new algorithms as "Modules". Implemented Modules Evolutionary Algorithms: - CMA-ES - (1+1)-ES - Differential Evolution Deterministic optimization algorithm: - SIMPLEX Learning: - a simple Artificial Neural Net Optimization problems: - test functions - interface for executing other programs (solvers) - parallel execution of problems - distributed execution of problems via socket connection between computers Others: - data storage - data analyser and viewer -
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Play-With-Sort-OC
Repository implemented in Objective-C with sorting algorithms
Play-With-Sort-OC is a learning-oriented repository implemented in Objective-C that demonstrates several classic sorting algorithms with code examples (selection sort, bubble sort, insertion sort, quick sort variants, heap sort, etc). The goal is educational; by showing how each algorithm works with animations or clear visualizations in an iOS/Objective-C context, the author helps developers understand not just the “how” but also the “why” behind each algorithm. -
Failed Payment Recovery for Subscription BusinessesFlexPay’s innovative platform uses multiple technologies to achieve the highest number of retained customers, resulting in reduced involuntary churn, longer life span after recovery, and higher revenue. Leading brands like LegalZoom, Hooked on Phonics, and ClinicSense trust FlexPay to recover failed payments, reduce churn, and increase customer lifetime value.
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TextTeaser
TextTeaser is an automatic summarization algorithm
textteaser is an automatic text summarization algorithm implemented in Python. It extracts the most important sentences from an article to generate concise summaries that retain the core meaning of the original text. The algorithm uses features such as sentence length, keyword frequency, and position within the document to determine which sentences are most relevant. By combining these features with a simple scoring mechanism, it produces summaries that are both readable and informative. ... -
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Algorithms in Python
Data Structures and Algorithms in Python
...Because it’s openly maintained, you can browse through issues, see test cases, and observe coding style in a “learning through code” fashion. It also serves as a playground where you can add problems, measure performance, and compare different algorithmic approaches. For anyone striving to move from “I know the syntax” to “I know how to use the right algorithm at the right time,” this repository is a practical asset. -
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go-best-practice
Trying to complete over 100 projects in various categories in golang
go-best-practice is essentially a Go book and code collection called “Go 实战开发” (“Go in Practice”), born from the idea of building over 100 practical projects in different categories using Go. It combines an ebook/zh directory with written chapters and a src directory that holds the corresponding source code, so readers can move seamlessly between theory and practice. The goal is to help developers go beyond basic syntax and actually build real applications, drawing inspiration from similar... -
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Attitude Estimator
A C++ implementation of a nonlinear 3D IMU fusion algorithm.
Attitude Estimator is a generic platform-independent C++ library that implements an IMU sensor fusion algorithm. Up to 3-axis gyroscope, accelerometer and magnetometer data can be processed into a full 3D quaternion orientation estimate, with the use of a nonlinear Passive Complementary Filter. The library is targeted at robotic applications, but is by no means limited to this. Features of the estimator include gyro bias estimation, transient quick learning, multiple estimation algorithms, tuneable estimator parameters, and near-global stability backed by theoretical analysis. ... -
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ProximityForest
Efficient Approximate Nearest Neighbors for General Metric Spaces
A proximity forest is a data structure that allows for efficient computation of approximate nearest neighbors of arbitrary data elements in a metric space. See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. Draper, "Scalable Action Recognition with a Subspace Forest," IEEE Conference on Computer... -
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csg.js
Constructive solid geometry on meshes using BSP trees in JavaScript
...With CSG, you build complex 3D shapes by combining primitives using Boolean operations like union, subtract, and intersect. The library focuses on clarity and correctness: its implementation is intentionally concise and readable so developers can understand the algorithm, while still correctly handling tricky edge cases such as overlapping coplanar polygons. A WebGL-based demo shows how two solids can be combined interactively in the browser, making it a great educational tool for learning CSG concepts. The API allows you to create primitives (cubes, spheres, etc.) and then combine or transform them programmatically, producing new mesh geometry for rendering or export. ... -
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The Free Connectionist Q-learning Java Framework is an library for developing learning systems. Keywords: qlearning, artificial intelligence, alife, neural nets, neural networks, machine learning, reinforcement learning unsupervised learning agents lejos
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Classic game solved with MinMax algorithm (full solution tree) and simple Heuristics. Specially for learning and teaching computer AI
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KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
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A Java implementation of the NEAT algorithm as created by Kenneth O Stanley. Also provides a toolkit for further experiments to be created and can provide both local and distributed learning environments.
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MultiBoost is a C++ implementation of the multi-class AdaBoost algorithm. AdaBoost is a powerful meta-learning algorithm commonly used in machine learning. The code is well documented and easy to extend, especially for adding new weak learners.
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