Search Results for "dl"
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Showing 14 open source projects for "dl"
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gallery-dl
Command-line program to download image galleries and collections
gallery-dl is a powerful command-line tool designed to download image galleries and collections from a wide range of image hosting and media websites. Built with Python, it works across multiple operating systems including Windows, Linux, and macOS. The program allows users to download images, manga chapters, or media collections by simply providing a supported website URL. -
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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. The content spans foundational models, architectures, and training methodologies across... -
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Open Video Downloader
A cross-platform GUI for youtube-dl made in Electron and node.js
A cross-platform GUI for youtube-dl made in Electron and node.js. Download from all kind of platforms: YouTube, vimeo, twitter & many more. Download multiple videos/playlists/channels in one go. Select the resolution and format you want to download in. Download private videos (currently only tested on YouTube). Multithreaded, up to 32 videos can be downloaded synchronously. -
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Totally Built Linux Distro
build linux from termcap to GTK-4.7 100% non-stop
Build all of a light linux distro non-stop and no buildfails with just a few commands. (not including un-tarring initial DL) Current Build Time: 3 to 4.7 hours* on an iCore7 using -j8 It's all automatic from Termcap to Gtk-4 and making new USB, it's new enough run firefox 20-130 and Mathematica 4 - 14. Minimal commandlines and configuration required; just a few in itself. Cross Compiles i386 to x86_64 (note not a canadian cross). ~500 pkgs built including configured database sendmail and apache. ... -
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MELO
Machine Executable Language Ontology (MELO)
This project is intended to fill the gap between the semantic web and the mainstream of software engineering, especially to integrate the semantic web with programming languages, and find an ontological representation of programming languages, including abstract syntax code execution, and global interoperability in execution environments. The machine executable language is modelled in OWL 2 DL using OWL API in C++ developed in this project. -
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Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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irs
A music downloader that understands your metadata needs
...It does this by interfacing with the Spotify API, grabbing metadata, and then searching Youtube for a video containing the song's audio. It will download the video using youtube-dl, extract the audio using ffmpeg, and then pack the audio and metadata together into an MP3. From the core, it has been extended to download the index of albums and playlists through the Spotify API, and then iteratively use the method described for downloading each song. -
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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... -
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Tensor2Tensor
Library of deep learning models and datasets
Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and compare the results. ... -
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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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Formagic moved to GitHub. Please visit https://github.com/Weasle/Formagic/ to stay up to date. Formagic is an easy to use, fast and highly extensible HTML form generator written in PHP5. Formagic provides a framework for validating and filtering user input with very little effort.
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Implementation of Damerau-Levenshtein fuzzy string matching in Java. Returns the distance adding one point per character insert, deletion, mismatche and swap.. This is an extension of apache/commons/lang/StringUtils.getLevenshteinDistance()
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XML schemas, XMLBeans, and Java implementation of the DIG interface -- a standardised XML interface to Description Logics systems developed by the DL Implementation Group (DIG).
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DL was designed to be a pure data language, built on very simple constructs, and internally representing typed values rather than depending on external schemas to infer type values.
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