Search Results for "python data analysis" - Page 18
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Showing 998 open source projects for "python data analysis"
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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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ProxyPool
An Efficient ProxyPool with Getter, Tester and Server
Simple and efficient proxy pool, providing the following functions. Regularly crawl free proxy websites, easy and scalable. Use Redis to store brokers and sort broker availability. Regular testing and screening to eliminate unavailable proxies and leave available proxies. Provides a proxy API to randomly select available proxies that pass the test. The principle analysis of the proxy pool can be seen in " How to Build an Efficient Proxy Pool ". It is recommended to read it before using it.... -
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Code Maat
A command line tool to mine and analyze data from version-control
Code Maat is a command-line tool for analyzing version-control systems (Git, SVN, etc.) to uncover code health insights—development hotspots, author coupling, and temporal change metrics. Created by Adam Tornhill, it supports research in behavioral code analysis and is often paired with his books like Code as a Crime Scene and Software Design X‑Rays. -
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Cinemagoer
Python package to retrieve and manage data of the IMDb
Cinemagoer is a Python package useful to retrieve and manage the data of the IMDb movie database about movies, people, characters and companies. Platform-independent, it can retrieve data from both the IMDb's web server and a local copy of the whole db. -
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LBRY SDK
The LBRY SDK for building decentralized content apps
...It utilizes the LBRY blockchain as a global namespace and database of digital content. Blockchain entries contain searchable content metadata, identities, rights and access rules. LBRY also provides a data network that consists of peers (seeders) uploading and downloading data from other peers, possibly in exchange for payments, as well as a distributed hash table used by peers to discover other peers. LBRY SDK for Python is currently the most fully featured implementation of the LBRY Network protocols and includes many useful components and tools for building decentralized applications. -
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Data science blogs
A curated list of data science blogs
Data Science Blogs is a curated repository that aggregates a wide range of high-quality blogs and resources related to data science, machine learning, and analytics into a single organized collection. It serves as a discovery platform for practitioners, researchers, and learners who want to stay updated with industry trends, techniques, and insights without manually searching for reliable sources. The repository includes links to personal blogs, professional publications, and educational... -
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Hydrogen
Run code interactively, inspect data, and plot
Hydrogen is an interactive coding environment that supports Python, R, JavaScript and other Jupyter kernels. Hydrogen was inspired by Bret Victor's ideas about the power of instantaneous feedback and the design of Light Table. Running code inline and in real-time is a more natural way to develop. By bringing the interactive style of Light Table to the rock-solid usability of Atom, Hydrogen makes it easy to write code the way you want to. You also may be interested in our latest project –... -
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unfetch
Bare minimum 500b fetch polyfill
Tiny 500b fetch "barely-polyfill". With a module bundler like rollup or webpack, you can import unfetch to use in your code without modifying any globals. While one of Unfetch's goals is to provide a familiar interface, its API may differ from other fetch polyfills/ponyfills. One of the key differences is that Unfetch focuses on implementing the fetch() API, while offering minimal (yet functional) support to the other sections of the Fetch spec, like the Headers class or the Response class.... -
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quantitative
Quantized transactions python3
...The README and associated lessons walk the user through implementing algorithms, likely covering data handling, backtesting, and maybe simple trading logic. As an open-source educational resource, it’s designed for Python users interested in automatic trading, algorithmic strategies, and financial data analysis. -
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UnionML
Build and deploy machine learning microservices
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. -
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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. -
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Twinify
Privacy-preserving generation of a synthetic twin to a data set
twinify is a software package for the privacy-preserving generation of a synthetic twin to a given sensitive tabular data set. On a high level, twinify follows the differentially private data-sharing process introduced by Jälkö et al.. Depending on the nature of your data, twinify implements either the NAPSU-MQ approach described by Räisä et al. or finds an approximate parameter posterior for any probabilistic model you formulated using differentially private variational inference (DPVI).... -
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Wooey
A Django app that creates automatic web UIs for Python scripts
...Enable the easy wrapping of any program in simple python instead of having to use language specific to existing tools such as Galaxy. Enable fellow lab members with no command line experience to utilize python scripts. Autodocument workflows for data analysis (simple model saving). -
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FairScale
PyTorch extensions for high performance and large scale training
FairScale is a collection of PyTorch performance and scaling primitives that pioneered many of the ideas now used for large-model training. It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce... -
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RedtDec
RetDec is a retargetable machine-code decompiler based on LLVM
...Demangling of symbols from C++ binaries (GCC, MSVC, Borland). Reconstruction of functions, types, and high-level constructs. Output in two high-level languages: C and a Python-like language. Generation of call graphs, control-flow graphs, and various statistics. Detection and reconstruction of C++ class hierarchies (RTTI, vtables). Signature-based removal of statically linked library code. Static analysis of executable files with detailed information. We currently support Windows (7 or later), Linux, macOS, and (experimentally) FreeBSD. ... -
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Blue Print
Blue Print is a remote access, cross-platform hex editor/data analyzer
...Users can start the back-end of WBP on PC/server/NAS/smart device(hereinafter referred to as the host) which has network connection, and perform graphical editing & analysis on data of the host in a browser on any other machine regardless of whether the host has local graphics module or not. Of course, you can also operate directly on host which has local graphics module. -
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Name-That-Hash
Identify MD5, SHA256 and 300+ other hashes
...One of its core ideas is popularity-aware ranking: when you feed in a hash, it prioritizes likely real-world types such as NTLM over obscure ones like Skype hashes, instead of treating them equally. The tool provides concise “hash summaries” that explain where a given hash format is commonly used, helping users decide how to proceed with cracking or further analysis. Name-That-Hash is accessible via a Python CLI (nth) and also exposes an API and JSON output, making it easy to plug into other tools or workflows, and there is also a web app that requires no local installation. -
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OpenCensus Libraries for Go
A stats collection and distributed tracing framework
OpenCensus and OpenTracing have merged to form OpenTelemetry, which serves as the next major version of OpenCensus and OpenTracing. OpenCensus is a set of libraries for various languages that allow you to collect application metrics and distributed traces, then transfer the data to a backend of your choice in real time. This data can be analyzed by developers and admins to understand the health of the application and debug problems. -
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DeepCTR
Package of deep-learning based CTR models
DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can be used to easily build custom models. You can use any complex model with model.fit(), and model.predict(). Provide tf.keras.Model like interface for quick experiment. Provide tensorflow estimator interface for large scale data and distributed training. It is compatible with both tf 1.x and tf 2.x. With the great success of deep learning,DNN-based... -
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DeepCTR-Torch
Easy-to-use,Modular and Extendible package of deep-learning models
DeepCTR-Torch is an easy-to-use, Modular and Extendible package of deep-learning-based CTR models along with lots of core components layers that can be used to build your own custom model easily.It is compatible with PyTorch.You can use any complex model with model.fit() and model.predict(). With the great success of deep learning, DNN-based techniques have been widely used in CTR estimation tasks. The data in the CTR estimation task usually includes high sparse,high cardinality categorical... -
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Security Code Scan
Vulnerability Patterns Detector for C# and VB.NET
Detects various security vulnerability patterns. SQL Injection, Cross-Site Scripting (XSS), Cross-Site Request Forgery (CSRF), XML eXternal Entity Injection (XXE), etc. Inter-procedural taint analysis for input data. Continuous Integration (CI) support for GitHub and GitLab pipelines. Stand-alone runner or through MSBuild for custom integrations. Analyzes .NET and .NET Core projects in the background (IntelliSense) or during a build. Works with Visual Studio 2019 or higher. Visual Studio Community, Professional and Enterprise editions are supported. ... -
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Amazon SageMaker Operators Kubernetes
Amazon SageMaker operator for Kubernetes
Amazon SageMaker is a fully managed machine learning service. With SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment. It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so you don't have to manage servers. It also provides common machine learning algorithms that are optimized to run efficiently against extremely large data in a distributed environment. ... -
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Jraph
A Graph Neural Network Library in Jax
Jraph (pronounced “giraffe”) is a lightweight JAX library developed by Google DeepMind for building and experimenting with graph neural networks (GNNs). It provides an efficient and flexible framework for representing, manipulating, and training models on graph-structured data. The core of Jraph is the GraphsTuple data structure, which enables users to define graphs with arbitrary node, edge, and global attributes, and to batch variable-sized graphs efficiently for JAX’s just-in-time... -
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Sandia Cyber Omni Tracker
Sandia Cyber Omni Tracker (SCOT)
SCOT is an open-source cybersecurity incident response and threat intelligence management system developed by Sandia National Laboratories. It centralizes alert collection, facilitates team collaboration, and enriches data with automated analysis, enhancing the efficiency and effectiveness of security operations teams. -
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Blend_My_NFTs
Easily generate thousands of 3D models, images, and animation NFTs
Blend_My_NFTs is an open-source, free-to-use Blender add-on that enables you to easily generate thousands of 3D Models, Animations, and Images. This add-on's primary purpose is to aid in the creation of large generative 3D NFT collections. It is the first and easiest 3D NFT generator. Blend_My_NFTs was initially developed to create Cozy Place, an NFT collection by This Cozy Studio Inc. Blend_My_NFTs works with Blender 3.2.2 on Windows 10 or macOS Big Sur 11.6. Linux is supported, however we...
