Search Results for "deep" - Page 3
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105 projects for "deep" with 2 filters applied:
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Scalable-Software-Architecture
Collection of tech talks, papers and web links on Distributed Systems
Scalable-Software-Architecture gathers tech talks, academic papers, blog posts and web links related to building scalable software architecture, distributed systems, system design, and production-scale considerations. The aim is to help readers study how large systems operate: how to scale them, how to handle latency, failure, load, concurrency, and how to structure software for maintainability at scale. Because many interview and real-world engineering problems revolve around system design... -
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deep-clean
When Gradle or the IDE let you down, just --nuke all them caches
A Kotlin script that nukes all build caches from Gradle/Android projects. Useful when Gradle or the IDE let you down. The script has been tested on macOS, but it is completely untested on Linux and Windows. KScript may not work at all on Windows! For this script to work, you need to have kotlin, script, and maven on your PATH. If you don't have all three commands on your PATH, then read on to the next section to install them. To make the script run, we'll first need to install all the... -
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Common Resource Grep - crgrep
Common Resource Grep
CRGREP searches for matching text in databases, various document formats, archives and other difficult to access resources. A command line tool for name and content text matching in database tables, plain files, MS Office documents, PDF, archives, MP3 audio, image meta-data, scanned documents, maven dependencies and web resources. CRGREP will search resources within resources of any arbitrary combination or depth, so text within a document within a zip archive, and so on. Here you... -
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Neural Network Visualization
Project for processing neural networks and rendering to gain insights
nn_vis is a minimalist visualization tool for neural networks written in Python using OpenGL and Pygame. It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. Its lightweight codebase is great for customization and teaching purposes. -
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graphql-api-koa
GraphQL execution and error handling middleware written from scratch
GraphQL execution and error handling middleware written from scratch for Koa. -
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ml-surveys
Survey papers summarizing advances in deep learning, NLP, CV, graphs
The ml-surveys repository is a broad, maintainable overview of survey papers across many subfields of machine learning — including deep learning, NLP, computer vision, graph ML, reinforcement learning, recommendation systems, embeddings, meta-learning, and more. Instead of diving into code or experiments, this repo gathers authoritative survey and review articles, summarizing the state-of-the-art, trends, challenges, and directions within each subdomain. For someone trying to get up to speed with a new ML subfield — say graph neural networks or meta-learning — ml-surveys offers a curated reading list of foundational and recent works, helping map the landscape quickly. ... -
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Reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI
...It’s structured to serve learners progressing from basic tabular methods to function approximation and deep learning extensions, making it suitable for students, researchers, or practitioners exploring reinforcement learning fundamentals. -
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CommandlineConfig
A library for users to write configurations in Python
...One of its core strengths is the ability to override configuration values directly from the command line, making it convenient to run many experimental variants without editing files repeatedly. The library supports arbitrarily deep nested structures, type handling, enumerated value constraints, and even tuple types, which are common in ML experiment setups. It also includes features for automatic version checking and convenient help output, so users can quickly see available parameters and their descriptions via a -h flag. -
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pyTorch Tutorials
Build your neural network easy and fast
pyTorch Tutorials is an open-source collection of hands-on tutorials designed to teach developers how to build neural networks with the PyTorch framework. It covers the fundamentals of PyTorch from basic tensor operations to constructing full neural network models, making it suitable for beginners and intermediate learners alike. The project is structured around clear, executable Python scripts and Jupyter notebooks that demonstrate regression, classification, convolutional networks,... -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple computational steps, while maintaining speaker consistency across output channels. ... -
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deeplinks.js
Simple deep links to any selection of text on your website
deeplinks.js allows people to easily link directly to any text selection on your website. Here's an example of what one of these links looks like. It's intended mostly for blogs and other such websites, but it's relatively agnostic to the environment it's running in. People can select text on the site as the normally would, and when they do, the fragment identifier (the thing that comes after the # in the URL) changes. If they want to share the text they have selected, they simply copy the... -
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TensorFlow Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TensorFlow Examples is a comprehensive repository of example implementations, tutorials, and reference code intended to help newcomers and intermediate learners dive into TensorFlow quickly. It contains both Jupyter notebooks and raw source code, covering a broad range of tasks: from basic machine-learning and neural-network models to more advanced use cases, using both TensorFlow v1 and v2 APIs. For clarity and educational value, each example is accompanied by explanatory comments or... -
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libpython-clj
Python bindings for Clojure
libpython-clj is a deep interop library enabling you to load and use Python modules from within Clojure as if they were native namespaces—and even extend Python objects from Clojure. It bridges to the Python C API, preserving REPL‑based workflows. Bridge between JVM objects and Python objects easily; use Python in your Java and use some Java in your Python. -
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PyTorchVideo
A deep learning library for video understanding research
PyTorchVideo is a deep learning library for video understanding, providing modular components and pretrained models for tasks like action recognition, video classification, detection, and self-supervised learning. It is tightly integrated with PyTorch and PyTorch Lightning, offering flexible APIs for building and training spatiotemporal networks. The library includes efficient implementations of state-of-the-art architectures such as SlowFast, X3D, and MViT, optimized for both research prototyping and production inference. ... -
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Arraymancer
A fast, ergonomic and portable tensor library in Nim
Arraymancer is a tensor and deep learning library for the Nim programming language, designed for high-performance numerical computations and machine learning applications. -
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BifurcumLib
A library for running through a directional graph.
This is the library for the project Bifurcum. It does all the work. It has a simple algorithm (Deep First Search with modifications) and allows sorting children before traversing. This library sums up the authors 4-years experience when programming a commercial tool for graph traversing (which used a much more advanced algorithm) and coaching its users. -
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CodeQL
Libraries and queries that power security researchers
...Instead of just pattern matching text, CodeQL ingests source code, builds rich representations of structure and data flow, and allows queries that reason about control flow, type systems, and interprocedural relationships. This makes it powerful not just for basic linting but for deep detection of complex security flaws like SQL injection, cross-site scripting, and taint propagation that traditional static analyzers can miss. CodeQL is used by security teams, developers, and open-source tooling to create reusable query libraries, enforce policy across repositories, and automate findings in CI/CD pipelines. -
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Top Deep Learning Projects
A list of popular github projects related to deep learning
TopDeepLearning is a curated index of the most popular GitHub projects related to deep learning, ranked by their star count. Rather than being a library itself, it serves as a curated roadmap and reference guide for anyone exploring the deep learning ecosystem — from beginners to experienced practitioners. By aggregating high-star projects across frameworks (TensorFlow, PyTorch), tools (computer vision, NLP, reinforcement learning), tutorials, and research code, it helps users quickly discover reputable and well-maintained repositories. ... -
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ResNeXt
Implementation of a classification framework
ResNeXt is a deep neural network architecture for image classification built on the idea of aggregated residual transformations. Instead of simply increasing depth or width, ResNeXt introduces a new dimension called cardinality, which refers to the number of parallel transformation paths (i.e. the number of “branches”) that are aggregated together. -
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benchm-ml
A benchmark of commonly used open source implementations
...It targets large scale settings by varying the number of observations (n) up to millions and the number of features (after expansion) to about a thousand, to stress test different implementations. The benchmarks cover algorithms like logistic regression, random forest, gradient boosting, and deep neural networks, and they compare across toolkits such as scikit-learn, R packages, xgboost, H2O, Spark MLlib, etc. The repository is structured in logical folders, each corresponding to algorithm categories. -
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pytorch-examples
Simple examples to introduce PyTorch
...By emphasizing readable code, the repository helps users understand how PyTorch’s imperative programming style enables flexible model development. It also serves as a quick reference for common patterns and techniques used in deep learning workflows. The project aligns with PyTorch’s philosophy of combining usability with performance and flexibility. Overall, pytorch-examples is an essential learning resource for anyone working with PyTorch. -
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Personal Blog
One article per week, the content is concise, neither salty nor light
...It uses Markdown files and a static-site setup (with configuration like _config.yml) to organize posts about Java back-end engineering, distributed systems, and source-code deep dives. The README and index emphasize that the blog (in this repo) is paused and that new content is primarily delivered via the WeChat channel, but the GitHub repo remains the canonical archive of links and categories. Articles are grouped by topic domains such as architecture, Spring Boot, Spring Cloud, Dubbo, Hystrix, Kafka, Redis, gateways, microservices, JVM tuning, and data structures, with each entry linking out to full posts on iocoder.cn. ... -
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Liberator
Liberator is a Clojure library for building RESTful applications
Liberator is a Clojure library designed for building RESTful web APIs in a principled, declarative manner. It abstracts HTTP semantics into resource constructs driven by representational state transfer, allowing deep control over HTTP behavior and content negotiation. Liberator used to be known as compojure-rest. It got renamed in July 2012. Liberator is loosely modeled after WebMachine and shares the same aims as Bishop. The examples in this document rely on you installing Leiningen 2. -
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PLEASE NOTE that we are in the process of moving to GitHub: https://github.com/jasypt/jasypt Jasypt (Java Simplified Encryption) is a java library which allows the developer to add basic encryption capabilities to his/her projects with minimum effort, and without the need of having deep knowledge on how cryptography works. PLEASE NOTE that we are in the process of moving to GitHub: https://github.com/jasypt/jasypt
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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 distributed computing topics, helping you bridge from basics to production-adjacent workflows. ...
