Showing 687 open source projects for "deep learning"

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  • 1
    Deep Learning Is Nothing

    Deep Learning Is Nothing

    Deep learning concepts in an approachable style

    Deep-Learning-Is-Nothing presents deep learning concepts in an approachable, from-scratch style that demystifies the stack behind modern models. It typically begins with linear algebra, calculus, and optimization refreshers before moving to perceptrons, multilayer networks, and gradient-based training. Implementations favor small, readable examples—often NumPy first—to show how forward and backward passes work without depending solely on high-level frameworks. ...
    Downloads: 0 This Week
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  • 2
    AWS Deep Learning Containers

    AWS Deep Learning Containers

    A set of Docker images for training and serving models in TensorFlow

    AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR).
    Downloads: 7 This Week
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  • 3
    Companion notebooks for Deep Learning

    Companion notebooks for Deep Learning

    Jupyter notebooks for the code samples of the book

    ...The material is designed to be accessible while still covering advanced topics, making it suitable for both beginners and intermediate practitioners. It leverages modern libraries and frameworks to demonstrate real-world applications of deep learning techniques. The notebooks also emphasize best practices in model training, evaluation, and deployment. Overall, this project serves as a comprehensive educational resource for learning deep learning through practical experimentation.
    Downloads: 4 This Week
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  • 4
    The Machine & Deep Learning Compendium

    The Machine & Deep Learning Compendium

    List of references in my private & single document

    The Machine & Deep Learning Compendium is an open-source knowledge repository that compiles summaries, references, and learning materials related to machine learning and deep learning. The project functions as a comprehensive compendium that organizes hundreds of topics covering algorithms, frameworks, research areas, and practical machine learning workflows.
    Downloads: 1 This Week
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  • 5
    imgclsmob Deep learning networks

    imgclsmob Deep learning networks

    Sandbox for training deep learning networks

    imgclsmob is a deep learning research repository focused on implementing and experimenting with convolutional neural networks for computer vision tasks. The project serves as a sandbox for training and evaluating a wide variety of neural network architectures used in image analysis. It includes implementations of models used for tasks such as image classification, object detection, semantic segmentation, and pose estimation.
    Downloads: 0 This Week
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  • 6
    Deep Learning Interviews book

    Deep Learning Interviews book

    Hundreds of fully solved job interview questions

    The interviews.ai repository hosts the open materials for the book Deep Learning Interviews, a comprehensive collection of technical questions and fully solved problems covering many aspects of artificial intelligence. The project was created to help students, researchers, and engineers prepare for machine learning and deep learning interviews by providing structured explanations of key concepts. The repository organizes problems across topics such as neural networks, optimization, probabilistic models, and mathematical foundations of machine learning.
    Downloads: 0 This Week
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  • 7
    Learn PyTorch for Deep Learning

    Learn PyTorch for Deep Learning

    Materials for the Learn PyTorch for Deep Learning

    Learn PyTorch for Deep Learning is an open-source educational repository that provides the full learning materials for the “Learn PyTorch for Deep Learning: Zero to Mastery” course created by Daniel Bourke. The project is designed to teach beginners how to build deep learning models using PyTorch through a hands-on, code-first learning approach. Instead of focusing heavily on theory alone, the repository encourages learners to experiment with code and develop practical machine learning skills through guided examples and exercises. ...
    Downloads: 0 This Week
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  • 8
    Deep Learning Essay Reading

    Deep Learning Essay Reading

    Read classic and new deep learning papers paragraph by paragraph

    Deep Learning Essay Reading repository is a comprehensive collection of machine learning and deep learning research summaries designed to make cutting-edge academic work more accessible. Instead of reading entire dense academic papers, contributors provide structured breakdowns and insights into the most influential research from the past decade, often including explanation highlights and key takeaways.
    Downloads: 0 This Week
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  • 9
    Deep-Learning-Interview-Book

    Deep-Learning-Interview-Book

    Interview guide for machine learning, mathematics, and deep learning

    Deep-Learning-Interview-Book collects structured notes, Q&A, and concept summaries tailored to deep-learning interviews, turning scattered study into a coherent playbook. It spans the core math (linear algebra, probability, optimization) and the practitioner topics candidates actually face, like CNNs, RNNs/Transformers, attention, regularization, and training tricks.
    Downloads: 0 This Week
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  • 10
    satellite-image-deep-learning

    satellite-image-deep-learning

    Resources for deep learning with satellite & aerial imagery

    This page lists resources for performing deep learning on satellite imagery. To a lesser extent classical Machine learning (e.g. random forests) are also discussed, as are classical image processing techniques. Note there is a huge volume of academic literature published on these topics, and this repository does not seek to index them all but rather list approachable resources with published code that will benefit both the research and developer communities.
    Downloads: 0 This Week
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  • 11
    Deep Lake

    Deep Lake

    Data Lake for Deep Learning. Build, manage, and query datasets

    Deep Lake (formerly known as Activeloop Hub) is a data lake for deep learning applications. Our open-source dataset format is optimized for rapid streaming and querying of data while training models at scale, and it includes a simple API for creating, storing, and collaborating on AI datasets of any size. It can be deployed locally or in the cloud, and it enables you to store all of your data in one place, ranging from simple annotations to large videos.
    Downloads: 0 This Week
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  • 12
    Super comprehensive deep learning notes

    Super comprehensive deep learning notes

    Super Comprehensive Deep Learning Notes

    Super comprehensive deep learning notes is a massive and well-structured collection of deep learning notebooks that serve as a comprehensive study resource for anyone wanting to learn or reinforce concepts in computer vision, natural language processing, deep learning architectures, and even large-model agents. The repository contains hundreds of Jupyter notebooks that are richly annotated and organized by topic, progressing from basic Python and PyTorch fundamentals to advanced neural network designs like ResNet, transformers, and object detection algorithms. ...
    Downloads: 3 This Week
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  • 13
    Stock prediction deep neural learning

    Stock prediction deep neural learning

    Predicting stock prices using a TensorFlow LSTM

    ...The fluctuations in stock prices are driven by the forces of supply and demand, which can be unpredictable at times. To identify patterns and trends in stock prices, deep learning techniques can be used for machine learning. Long short-term memory (LSTM) is a type of recurrent neural network (RNN) that is specifically designed for sequence modeling and prediction.
    Downloads: 3 This Week
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  • 14
    Downloads: 0 This Week
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  • 15
    Zero to Mastery Deep Learning TensorFlow

    Zero to Mastery Deep Learning TensorFlow

    All course materials for the Zero to Mastery Deep Learning with TF

    This project is a comprehensive, code-first deep learning curriculum built around TensorFlow and Keras, designed to guide learners from foundational concepts to practical model deployment through hands-on experimentation. It is structured as a series of progressively complex Jupyter notebooks that emphasize writing and understanding code before diving into theory, reinforcing learning through repetition and application.
    Downloads: 1 This Week
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  • 16
    Deep Java Library (DJL)

    Deep Java Library (DJL)

    An engine-agnostic deep learning framework in Java

    Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. DJL is designed to be easy to get started with and simple to use for Java developers. DJL provides native Java development experience and functions like any other regular Java library. You don't have to be a machine learning/deep learning expert to get started.
    Downloads: 0 This Week
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  • 17
    PyTorch

    PyTorch

    Open source machine learning framework

    ...PyTorch can be used as a replacement for Numpy, or as a deep learning research platform that provides optimum flexibility and speed.
    Downloads: 117 This Week
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  • 18
    MATLAB Deep Learning Model Hub

    MATLAB Deep Learning Model Hub

    Discover pretrained models for deep learning in MATLAB

    Discover pre-trained models for deep learning in MATLAB. Pretrained image classification networks have already learned to extract powerful and informative features from natural images. Use them as a starting point to learn a new task using transfer learning. Inputs are RGB images, the output is the predicted label and score.
    Downloads: 1 This Week
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  • 19
    Deep Learning Models

    Deep Learning Models

    A collection of various deep learning architectures, models, and tips

    This repository collects clear, well-documented implementations of deep learning models and training utilities written by Sebastian Raschka. The code favors readability and pedagogy: components are organized so you can trace data flow through layers, losses, optimizers, and evaluation. Examples span fundamental architectures—MLPs, CNNs, RNN/Transformers—and practical tasks like image classification or text modeling.
    Downloads: 0 This Week
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  • 20
    Keras

    Keras

    Python-based neural networks API

    Python Deep Learning library
    Downloads: 19 This Week
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  • 21
    Determined

    Determined

    Determined, deep learning training platform

    ...Deploy your model using Determined's built-in model registry. Easily share on-premise or cloud GPUs with your team. Determined’s cluster scheduling offers first-class support for deep learning and seamless spot instance support. Check out examples of how you can use Determined to train popular deep learning models at scale.
    Downloads: 24 This Week
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  • 22
    Synapse Machine Learning

    Synapse Machine Learning

    Simple and distributed Machine Learning

    SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit, and OpenCV. ...
    Downloads: 0 This Week
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  • 23
    Best-of Machine Learning with Python

    Best-of Machine Learning with Python

    A ranked list of awesome machine learning Python libraries

    ...If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome! General-purpose machine learning and deep learning frameworks.
    Downloads: 0 This Week
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  • 24
    PaddlePaddle

    PaddlePaddle

    PArallel Distributed Deep LEarning: Machine Learning Framework

    PaddlePaddle is an open source deep learning industrial platform with advanced technologies and a rich set of features that make innovation and application of deep learning easier. It is the only independent R&D deep learning platform in China, and has been widely adopted in various sectors including manufacturing, agriculture and enterprise service. PaddlePaddle covers core deep learning frameworks, basic model libraries, end-to-end development kits and more, with support for both dynamic and static graphs.
    Downloads: 0 This Week
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  • 25
    AtomAI

    AtomAI

    Deep and Machine Learning for Microscopy

    ...Ultimately, it aims to combine the power and flexibility of the PyTorch deep learning framework and the simplicity and intuitive nature of packages such as scikit-learn, with a focus on scientific data.
    Downloads: 6 This Week
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