Search Results for "machine learning python" - Page 25
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707 projects for "machine learning python" with 2 filters applied:
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Your monitoring isn't a stack. It's a pile. Fix that.Replace Datadog, New Relic, and Sentry without adding three more dashboards.
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Accelerated Feature Extraction Tool
A fast GPU accelerated feature extraction software for speech analysis
A fast feature extraction software tool for speech analysis and processing. It incorporates standard MFCC, PLP, and TRAPS features. The tool is a specially designed to process very large audio data sets. It uses GPU acceleration if compatible GPU available (CUDA as weel as OpenCL, NVIDIA, AMD, and Intel GPUs are supported). CPU SSE intrinsic instruction set is used in cases where no compatible GPU present. The output files are stored in HTK format. The software is developed at Department of... -
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IMAGINE
Biological image viewer and processor
Detection, enumeration, and sizing of biological organisms by image analysis. -
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nn22 Basic Neural Networks for Octave
Simple .m files, Basic Neural Networks study for Octave (or Matlab)
--> For a more detailed description check the README text under the 'Files' menu option :) The project consists of a few very simple .m files for a Basic Neural Networks study under Octave (or Matlab). The idea is to provide a context for beginners that will allow to develop neural networks, while at the same time get to see and feel the behavior of a basic neural networks' functioning. The code is completely open to be modified and may suit several scenarios. The code... -
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Qix
Machine Learning, Deep Learning, PostgreSQL, Distributed System
Qix is an open-source repository that aggregates resources related to artificial intelligence, machine learning, and deep learning development. The project is designed as a curated index of useful tools, frameworks, research papers, and learning materials that developers can use to explore the AI ecosystem. It organizes information about libraries, tutorials, datasets, and software tools used in modern AI research and development. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Java Machine Learning Library is a library of machine learning algorithms and related datasets. Machine learning techniques include: clustering, classification, feature selection, regression, data pre-processing, ensemble learning, voting, ...
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A2y
Automated Algorithm Synthesis
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ANNFiD
A forensic file identification tool using neural networks
Just carved a bunch of bytes and have no idea what they could be? Maybe ANNFiD can help. ANNFiD uses neural network to identify byte patterns. It can be trained and has a GUI to help in the process. The tool is still on a very early stage, but could improve exponentially with the help of the developer community -
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C-IL2P
Original C-IL2P
This is a C++ implementation of the original C-IL2P system, invented by Artur D'Avila Garcez and Gerson Zaverucha. C-IL2P is a neural-symbolic learning system which uses a propositional logic program to create a three-layer recursive neural network and uses back-propagation to learn from examples. -
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StabLe
An algorithm for learning stable graphical models from data
Stable Graphical Model Learning (StabLe) is an algorithm for learning the structure and parameters of stable graphical (SG) models from data. Stable random variables are motivated by the central limit theorem for densities with (potentially) unbounded variance and can be thought of as natural generalizations of the Gaussian distribution to skewed and heavy-tailed phenomenon. SG models are multi-variate stable distributions that represent Bayesian networks whose edges encode linear... -
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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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LPCforSOS is a machine learning framework with a special focus on structured output spaces and pairwise learning. It supports currently multiclass, ordinal, hierarchical, multi-label and label ranking classification settings.
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Consilium Sentence Suggestions Tools
Consilium – User Defined sentence Suggestion Tool.
There are many tools available in market which will provide spell correction or grammer correction while making documents, but very few tools are available which are providing sentence completion according to previously entered text. But this all are providing sentence complition suggestion for sentences which are oftenly or regularly used by all people in same manner. But in reality style of writing changes person to person. While our aim is to provide a sentence suggestion tool which... -
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ktree
clustering, machine learning, algorithms
This project has moved to github at http://lmwtree.devries.ninja. -
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This project develops a simple, fast and easy to use Python graph library using NumPy, Scipy and PySparse.
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An open-source C++ library of machine learning by New York University's machine learning lab, led by Yann LeCun. In particular, implementations of convolutional neural networks with energy-based models along with a GUI, demos and tutorials.
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Java application for training and deploying text processing applications such as part-of-speech taggers, based on a re-implementation of Brill's algorithm in Java.
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LExAu: Learning Expectations Autonomously. Library for on-line data driven statistical machine learning.
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jFAN2 project develops a Java API to use a neural network (neuro-fuzzy) called FAN (Free Associative Neurons). Its an reprogramed version of jFAN "https://sourceforge.net/projects/jfan/".
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Reactor Breeder
A Genetic Algorithm for Reactors in StarMade
This software uses a genetic algorithm to "evolve" reactor designs for Schema's space-simulation game, Star-Made (http://star-made.org/). One of the more unique aspects of the game is that ship power management is not as simple as filling a cube with power generation blocks. This mechanism leads to difficulties in getting maximal power generation out of such reactors. This program rectifies this issue by using a self-organizing variant of brute force search. Much of the search space is... -
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pySTEP or Python Strongly Typed gEnetic Programming: A light Genetic Programming API that allows the user to easily evolve populations of trees with precise grammatical and structural constraints.
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yacaree: Yet Another Closure-based Association Rules Experimentation Environment (Development stalled here, check out under Wiki to find where it went.)
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CoffeeMud For AI
CoffeeMudForAI is plaform to design AI in
...To provide a set of agents that non-technical people can play around with and get a feel for how various AI techniques work. CoffeeMudForAI goals 1. To provide a platform to study the non-robotic aspects of AI(AI Planning, inter-agent planning, muti-agent planning, Machine learning, etc.) 2. To provide a game-like platform so people coming from the game AI world can contribute to AI research. -
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The Information Extraction Plugin allows the use of information extraction techniques within RapidMiner. It can be seen as an interface between natural language and IE- or datamining-methods, by extracting interesting information out of documents.
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JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.
