Search Results for "ml-so1v" - Page 7
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Showing 173 open source projects for "ml-so1v"
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Context for your AI agentsBuild data pipelines that feed your AI models and agents without managing infrastructure. Crawl any website, transform content, and push directly to your preferred vector store. Use 10,000+ tools for RAG applications, AI assistants, and real-time knowledge bases. Monitor site changes, trigger workflows on new data, and keep your AIs fed with fresh, structured information. Cloud-native, API-first, and free to start until you need to scale.
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Scikit-learn Tutorial
An introductory tutorial for scikit-learn
Scikit-learn Tutorial contains the materials for Jake VanderPlas’s introductory scikit-learn tutorial, originally used at major Python conferences. It provides a collection of notebooks that walk attendees from basic machine-learning concepts into practical modeling using the scikit-learn library. The tutorial covers data preparation, model fitting, evaluation, and common algorithms such as classification, regression, clustering, and dimensionality reduction. It is designed for people who... -
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InfiFly 3D
InfiFly a ML based 3D game.
This is the 3D game. There is space ship and your aim is to control the ship using hand movement(left to right, & right to left) and prevent the ship from hitting the asteroids and. Every level has different environment for create optical illusion. -
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Texar
Toolkit for Machine Learning, Natural Language Processing
Texar is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar provides a library of easy-to-use ML modules and functionalities for composing whatever models and algorithms. The tool is designed for both researchers and practitioners for fast prototyping and experimentation. Texar was originally developed and is actively contributed by Petuum and CMU in collaboration with other institutes. A mirror of this repository is maintained by Petuum Open Source. ... -
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automl-gs
Provide an input CSV and a target field to predict, generate a model
...No black box: you can see exactly how the data is processed, and how the model is constructed, and you can make tweaks as necessary. automl-gs is an AutoML tool which, unlike Microsoft's NNI, Uber's Ludwig, and TPOT, offers a zero code/model definition interface to getting an optimized model and data transformation pipeline in multiple popular ML/DL frameworks, with minimal Python dependencies (pandas + scikit-learn + your framework of choice). automl-gs is designed for citizen data scientists and engineers without a deep statistical background under the philosophy that you don't need to know any modern data preprocessing and machine learning engineering techniques to create a powerful prediction workflow. -
Grafana: The open and composable observability platformGrafana is the open source analytics & monitoring solution for every database.
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Canorus
Music score editor
Canorus is a free cross-platform music score editor. It supports an unlimited number and length of staffs, polyphony, a MIDI playback of notes, chord markings, lyrics, import/export filters to formats like MIDI, MusicXML, ABC Music, MusiXTeX and LilyPond -
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
Data Science IPython Notebooks is a broad, curated set of Jupyter notebooks covering Python, data wrangling, visualization, machine learning, deep learning, and big data tools. It aims to be a practical map of the ecosystem, showing hands-on examples with libraries such as NumPy, pandas, matplotlib, scikit-learn, and others. Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action. Advanced sections touch on neural networks and... -
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reNamer
Rename files depending on their .extension
If you want to rename your dataset samples for ML and you might have a lot of them (you should btw) or maybe you need to set different enumeration for every .extension you have or you just want to rename some personal stuff I am glad you are here. This is how you can rename your files: - For every .extension in the target folder reNamer sets unique enumeration. - Randomly - With your set of parameters. -
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Awesome Math
This is the Curriculum for "How to Learn Mathematics Fast"
...It also suggests checkpoints and practice ideas so you can test comprehension and move forward with confidence. The structure is useful both for newcomers who want a starting plan and for practitioners filling specific gaps before tackling ML or deep learning. Overall, it acts as a compact study plan that turns “learn math” from a vague goal into a concrete, achievable path. -
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Zhao
A compilation of "The Princely Party Relationship Network"
zhao is a repository that consolidates research, data, and insights related to Zhao, which is likely an individual’s research collection, notes, or curated resources on deep learning, AI, or computational topics (name and content context suggest specialized study). The project may include code examples, experiment results, references to academic papers, mathematical notes, and supporting scripts to explore specific ML methods, benchmarks, or theoretical findings. Because it aggregates content associated with Zhao, the repository functions as a personal or shared knowledge base for readers who want insight into a body of research rather than a traditional software library. Depending on the specific subfolders, it could offer implementations of algorithms, dataset processing utilities, or notebooks that illustrate concepts. ... -
Axe Credit Portal - ACP- is axefinance’s future-proof AI-driven solution to digitalize the loan process from KYC to servicing, available as a locally hosted or cloud-based software.Founded in 2004, axefinance is a global market-leading software provider focused on credit risk automation for lenders looking to provide an efficient, competitive, and seamless omnichannel financing journey for all client segments (FI, Retail, Commercial, and Corporate.)
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DeepLearn
Implementation of research papers on Deep Learning+ NLP+ CV in Python
Welcome to DeepLearn. This repository contains an implementation of the following research papers on NLP, CV, ML, and deep learning. The required dependencies are mentioned in requirement.txt. I will also use dl-text modules for preparing the datasets. If you haven't use it, please do have a quick look at it. CV, transfer learning, representation learning. -
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EvalAI
Evaluating state of the art in AI
EvalAI is an open-source platform for evaluating and comparing machine learning (ML) and artificial intelligence (AI) algorithms at scale. We allow the creation of an arbitrary number of evaluation phases and dataset splits, compatibility using any programming language, and organizing results in both public and private leaderboards. Certain large-scale challenges need special computing capabilities for evaluation. -
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pyhanlp
Chinese participle
...The project focuses on making HanLP’s capabilities accessible through a Python-friendly API surface, so you can integrate NLP steps into data pipelines, notebooks, and downstream ML or information-extraction code. In practice, it serves as a bridge layer: Python calls are translated into the corresponding HanLP operations, so you can keep your application logic in Python while relying on HanLP’s implementations. It is especially useful when you need a pragmatic “get results quickly” NLP layer for segmentation, tagging, entity extraction, parsing, or keyword-style tasks rather than experimenting with model training from scratch. -
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Tangent
Source-to-source debuggable derivatives in pure Python
...Tangent is useful to researchers and students who not only want to write their models in Python, but also read and debug automatically-generated derivative code without sacrificing speed and flexibility. Tangent works on a large and growing subset of Python, provides extra autodiff features other Python ML libraries don't have, has reasonable performance, and is compatible with TensorFlow and NumPy. -
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e-Metis - ML
Modul za napovedovanje učnih težav.
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GUI for DEDA
GUI for DEmography Data Analysis
<This project has been completely rewrote and transformed into a new one: https://sourceforge.net/projects/deday/. 2013/06/26> The graphic user interface for DEDA (DEmography Data Analysis), a scientific software package fitting survivalship data to a number of distributions using maximum likelihood (ML) method. Currently, Weibull (2p), Gompertz and Gompertz-Makeham are supported. IMPORTANT NOTICE: Only the GUI is provided here. In order to perform the analysis, one also need the DEDA computation core program. Please email a request to me, entitled: 'Request for DEDA computation core', if you wish to have a copy. -
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Python Machine learning library with multi-core support. Wraps existing ML libraries in order to be able to run and analyse experiments with one front-end API. Currently supports MLP, GA, GP, ESN and RBF algorithms.
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ZML, the Zeitung Markup Language, is a simple CMS for small newspapers. It was specifically designed to publish a student newspaper in print and on the Web. It uses LaTeX and XHTML. So far, it is documented in German only.
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A library which provides the same functionality as the Python/C API detailed at python.org, thus allowing objective caml programmers to provide python modules as native ocaml code, as well as allowing ocaml code to use python extensions.
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ml_script provides a scripting interface for Winamp 5 media library. Currently, interfaces are available for Perl, Python and Ruby.
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Framework for software component integration, interoperability and adoptability through a XML based vocabulary: Software Component Integration Mark-up Language (SCIML)
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This project is for credit in UIUC's CS327 Software Engineering class. This is a class scheduler written in ocaml and python, using a web interface. The feature list will be decided as the project progresses.
