Showing 92 open source projects for "python q learning"

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  • 1
    ML workspace

    ML workspace

    All-in-one web-based IDE specialized for machine learning

    All-in-one web-based development environment for machine learning. The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard)...
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  • 2
    Data Science Notes

    Data Science Notes

    Curated collection of data science learning materials

    Data Science Notes is a large, curated collection of data science learning materials, with explanations, code snippets, and structured notes across the typical end-to-end workflow. It spans foundational math and statistics through data wrangling, visualization, machine learning, and practical project organization. The content emphasizes hands-on understanding by pairing narrative notes with runnable examples, making it useful for both self-study and classroom settings. Because it aggregates...
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  • 3
    Amazon SageMaker Examples

    Amazon SageMaker Examples

    Jupyter notebooks that demonstrate how to build models using SageMaker

    ...They have the familiar Jupyter and JuypterLab interfaces that work well for single users, or small teams where users are also administrators. Advanced users also use SageMaker solely with the AWS CLI and Python scripts using boto3 and/or the SageMaker Python SDK.
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  • 4
    AlphaPy

    AlphaPy

    Python AutoML for Trading Systems and Sports Betting

    AlphaPy is a Python-based AutoML framework tailored for trading systems and sports betting applications. Built on popular libraries like scikit-learn and pandas, it enables data scientists and speculators to craft predictive models, ensemble strategies, and automated forecasting systems with minimal setup. Run machine learning models using scikit-learn, Keras, xgboost, LightGBM, and CatBoost.
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  • 5

    Spectral Python

    A python module for hyperspectral image processing

    Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more.
    Downloads: 1 This Week
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  • 6
    StellarGraph

    StellarGraph

    Machine Learning on Graphs

    StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. ...
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  • 7
    SageMaker Containers

    SageMaker Containers

    Create SageMaker-compatible Docker containers

    Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. The SageMaker Training Toolkit can be easily added to...
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  • 8
    TensorWatch

    TensorWatch

    Debugging, monitoring and visualization for Python Machine Learning

    TensorWatch is an open source debugging and visualization platform created by Microsoft Research to support machine learning, deep learning, and reinforcement learning workflows. It enables developers to observe training behavior in real time through interactive visualizations, primarily within Jupyter Notebook environments. The tool treats most data interactions as streams, allowing flexible routing, storage, and visualization of metrics generated during model training. A distinctive...
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  • 9
    Deep Learning with PyTorch

    Deep Learning with PyTorch

    Latest techniques in deep learning and representation learning

    This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. The prerequisites include DS-GA 1001 Intro to Data Science or a graduate-level machine learning course.
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  • 10
    Inviwo

    Inviwo

    Interactive Visualization Workshop

    Inviwo is a modern, open-source visualization framework designed for interactive visual data analysis and scientific computing. Built in C++ with a modular, extensible architecture, Inviwo combines a visual editor (for creating data pipelines) with a powerful runtime engine that supports real-time rendering, interaction, and GPU-accelerated processing. It’s widely used in scientific domains for building and sharing visualizations of complex data such as medical imaging, simulations, and...
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  • 11
    Vaex

    Vaex

    Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python

    Data science solutions, insights, dashboards, machine learning, deployment. We start at 100GB. Vaex is a high-performance Python library for lazy Out-of-Core data frames (similar to Pandas), to visualize and explore big tabular datasets. It calculates statistics such as mean, sum, count, standard deviation etc, on an N-dimensional grid for more than a billion (10^9) samples/rows per second.
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  • 12
    AI learning

    AI learning

    AiLearning, data analysis plus machine learning practice

    We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community,...
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  • 13

    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.
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  • 14
    Rodeo

    Rodeo

    A data science IDE for Python

    ...Rodeo makes it very easy for its users to explore what is created by them and also alongside allows the users to Inspect, interact, compare data frames, plots and even much more. It is an IDE that has been built especially for data science/Machine Learning in Python and you can also very simply think of it as a light weight alternative to the IPython Notebook.
    Downloads: 1 This Week
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  • 15
    QuickNXS

    QuickNXS

    Polarized ToF reflectivity raw data analysis tool

    Data evaluation tool for the magnetism reflectometer at the spallation neutron source (BL-4A@SNS). Reads raw nexus files (HDF5) of histogrammed or event mode data to create reflectivity curves and 2D Q-maps.
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  • 16
    pySPACE

    pySPACE

    Signal Processing and Classification Environment in Python using YAML

    pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due...
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  • 17
    Monk Computer Vision

    Monk Computer Vision

    A low code unified framework for computer vision and deep learning

    Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers. There are three libraries in this opensource set. - Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms. - Monk Object Detection -...
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