778 projects for "machine learning python" with 2 filters applied:

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  • 1
    Computational Linear Algebra for Coders

    Computational Linear Algebra for Coders

    Free online textbook of Jupyter notebooks

    ...Instead of emphasizing purely theoretical mathematics, the project takes a programming-oriented approach that helps developers understand how linear algebra algorithms are implemented in real computational systems. The course explores topics such as matrix decomposition, numerical stability, and optimization techniques that are essential for machine learning and data science applications.
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  • 2
    Bolt ML

    Bolt ML

    10x faster matrix and vector operations

    Bolt is an open-source research project focused on accelerating machine learning and data mining workloads through efficient vector compression and approximate computation techniques. The core idea behind Bolt is to compress large collections of dense numeric vectors and perform mathematical operations directly on the compressed representations instead of decompressing them first. This approach significantly reduces both memory usage and computational overhead when working with high-dimensional data commonly used in machine learning systems. ...
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  • 3

    Training Image Operators from Samples

    Tools to train Image Operators automatically from a set of samples.

    TRIOS - Training Image Operators from Samples is a set of tools to bring Image Processing closer to scientists in general. It is capable of estimating an operator between two images using only pairs of samples that contain an input image and the desired output. The operator is saved to a file and can be applied to any image.
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  • 4
    bulbea

    bulbea

    Deep Learning based Python Library for Stock Market Prediction

    bulbea is an open-source Python library designed for financial analysis and stock market prediction using machine learning and deep learning techniques. The library provides tools for retrieving financial time series data, preprocessing market data, and training predictive models that estimate future price movements. bulbea integrates common machine learning frameworks such as TensorFlow and Keras to build neural network models capable of learning patterns in historical financial data. ...
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    Train ML Models With SQL You Already Know

    BigQuery automates data prep, analysis, and predictions with built-in AI assistance.

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  • 5
    The KReator project is a collection of software systems, tools, algorithms and data structures for logic-based knowledge representation. Currently, it includes the software systems KReator and MECore and the library Log4KR: - KReator is an integrated development environment (IDE) for relational probabilistic knowledge representation languages such as Bayesian Logic Programs (BLPs), Markov Logic Networks (MLNs), Relational Maximum Entropy (RME), First-Order Probabilistic...
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  • 6

    PyDaMelo

    Python-compatible Data mining elementary objects

    An attempt at offering machine learning and data mining algorithms at the finest grain we are able to, easy to combine together through Python scripting to glue together the Lego-like bricks.
    Downloads: 0 This Week
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  • 7
    H2O-3

    H2O-3

    H2O is an Open Source, Distributed, Fast & Scalable Machine Learning

    H2O-3 is an open-source machine learning platform designed to build scalable and distributed machine learning models across large datasets. The system operates as an in-memory computing platform that allows data scientists to train models quickly using distributed resources. It supports many machine learning algorithms including generalized linear models, gradient boosting machines, deep learning networks, and ensemble techniques. ...
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  • 8
    Neural Photo Editor

    Neural Photo Editor

    A simple interface for editing natural photos

    Neural Photo Editor is an experimental machine learning application that demonstrates how generative neural networks can be used as an interactive photo editing tool. The project implements the system described in the research paper Neural Photo Editing with Introspective Adversarial Networks, which introduces a generative model capable of modifying images in semantically meaningful ways.
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  • 9

    TEES

    Turku Event Extraction System

    Turku Event Extraction System (TEES) is a free and open source natural language processing system developed for the extraction of events and relations from biomedical text. It is written mostly in Python, and should work in generic Unix/Linux environments. Currently, the TEES source code repository still remains on GitHub at http://jbjorne.github.com/TEES/ where there is also a wiki with more information.
    Downloads: 13 This Week
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  • 10
    Speakable Programming for Every Language

    Speakable Programming for Every Language

    Your language to speak with all.

    This project has the language data for spel, the main new codebase is at: https://gitlab.com/liberit/pyac A computer programming language using human language syntax for human-to-human and human-to-computer communication with high precision, supporting many languages. Currently has alpha prototype support for analytic versions of the UN languages English, Mandarin Chinese, Spanish, Arabic, Russian...
    Downloads: 2 This Week
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  • 11
    Retrieval-Based Conversational Model

    Retrieval-Based Conversational Model

    Dual LSTM Encoder for Dialog Response Generation

    Retrieval-Based Conversational Model in Tensorflow is a project implementing a retrieval-based conversational model using a dual LSTM encoder architecture in TensorFlow, illustrating how neural networks can be trained to select appropriate responses from a fixed set of candidate replies rather than generate them from scratch. The core idea is to embed both the conversation context and potential replies into vector representations, then score how well each candidate fits the current dialogue,...
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  • 12

    LightPCC

    Parallel pairwise correlation computation on Intel Xeon Phi clusters

    The first parallel and distributed library for pairwise correlation/dependence computation on Intel Xeon Phi clusters. This library is written in C++ template classes and achieves high speed by exploring the SIMD-instruction-level and thread-level parallelism within Xeon Phis as well as accelerator-level parallelism among multiple Xeon Phis. To facilitate balanced workload distribution, we have proposed a general framework for symmetric all-pairs computation by building provable bijective...
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  • 13

    JCLTP

    A Java Class Library for Text Processing

    JCLTP is a class library designed for processing text. JCLTP is free, open source and developed with the Java programming language. JCLTP is distributed under the GNU license. It incorporates several technologies that enable process information while applying AI techniques, in order to build predictive models for text classification. Through a flexible structure of interfaces and classes, the opportunity to extend, adapt and add functionality JCLTP is provided. Thus, analysis of new types...
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  • 14
    GT NLP Class

    GT NLP Class

    Course materials for Georgia Tech CS 4650 and 7650

    This repository contains lecture notes, slides, assignments, and code for a university-level Natural Language Processing course. It spans core NLP topics such as language modeling, sequence tagging, parsing, semantics, and discourse, alongside modern machine learning methods used to solve them. Students work through programming exercises and problem sets that build intuition for both classical algorithms (like HMMs and CRFs) and neural approaches (like word embeddings and sequence models). The materials emphasize theory grounded in practical experimentation, often via Python notebooks or scripts that visualize results and encourage ablation studies. ...
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  • 15
    Spark Python Notebooks

    Spark Python Notebooks

    Apache Spark & Python (pySpark) tutorials for Big Data Analysis

    Spark Python Notebooks is a curated collection of example Jupyter notebooks designed to help developers and data engineers learn Apache Spark using Python in an interactive environment. Rather than only providing static code files, this project uses notebooks to teach practical data processing workflows, exposing users to real Spark programming patterns like working with RDDs, DataFrames, and distributed computations.
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  • 16
    AFNER is a C++ named entity recognition system that uses machine learning techniques. It is customisable to various domains. It also allows for multiple and overlapping named entity labels.
    Downloads: 0 This Week
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  • 17
    An open source optical flow algorithm framework for scientists and engineers alike.
    Downloads: 0 This Week
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  • 18
    BagaturChess

    BagaturChess

    Java Chess Engine

    This is UCI Chess Engine writen in Java. Since version 1.4 (inclusive) the project was moved to https://github.com/bagaturchess/Bagatur
    Downloads: 2 This Week
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  • 19

    jPrediction

    Open project ternary classifier of the machine learning

    Open project ternary classifier of the machine learning
    Downloads: 0 This Week
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  • 20
    libcrn is document image processing library written in C++11 for Linux, Windows, Mac OsX and Google Android. It is a toolbox that allows to create easily software such as OCRs and layout analysis tools.
    Downloads: 1 This Week
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  • 21
    A broad collection of command-line-interface tools for performing machine learning operations. Each tool is a thin wrapper around functionality in a well-documented C++ class library. Waffles tools are designed to be simple, script-friendly, and to
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  • 22
    Part-of-speech tagging is the task of assigning symbols from a particular set to words in a natural language text. ACOPOST implements and extends well-known machine learning techniques and provides a uniform environment for testing.
    Downloads: 1 This Week
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  • 23

    GA-EoC

    GeneticAlgorithm-based search for Heterogeneous Ensemble Combinations

    In data classification, there are no particular classifiers that perform consistently in every case. This is even worst in case of both the high dimensional and class-imbalanced datasets. To overcome the limitations of class-imbalanced data, we split the dataset using a random sub-sampling to balance them. Then, we apply the (alpha,beta)-k feature set method to select a better subset of features and combine their outputs to get a consolidated feature set for classifier training. To...
    Downloads: 0 This Week
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  • 24
    PyML is an interactive object oriented framework for machine learning written in python. PyML focuses on kernel classifiers, providing tools for feature selection, model selection, and methods for assessing classifier performance.
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  • 25
    openModeller is a complete C++ framework for species potential distribution modelling. The project also includes a graphical user interface, a web service interface and an API for Python.
    Downloads: 10 This Week
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