Search Results for "make" - Page 9
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Showing 893 open source projects for "make"
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AI Engineering Academy
Mastering Applied AI, One Concept at a Time
AI-Engineering.academy is a community-driven educational repository that organizes practical knowledge and learning paths for applied AI engineering. The project aims to make complex AI concepts accessible by structuring them into progressive learning modules covering topics such as prompt engineering, retrieval-augmented generation, LLM deployment, and AI agents. Rather than focusing purely on theoretical explanations, the repository emphasizes hands-on understanding of how modern AI systems are designed, built, and deployed in real-world applications. ... -
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SkillForge
Ultimate meta-skill for generating best-in-class Claude Code skills
...The system includes tooling that routes natural language inputs to existing skills, augments them, or generates new ones using autonomous phases, enforcing quality, extensibility, security, and timelessness. By codifying best practices into automated workflows, SkillForge aims to raise the standard of AI skill implementations and make them more robust, reliable, and maintainable. -
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Flan Scan
A pretty sweet vulnerability scanner
Flan Scan is a lightweight open-source network vulnerability scanner designed to make it easy to detect exposed services, open ports, and associated vulnerabilities across IP ranges or network segments as part of security audit and compliance workflows. It is essentially a thin wrapper around the widely-used Nmap scanner, augmenting it with scripts and tooling that transform raw Nmap output into vulnerability-focused reports that map detected services to known CVEs, making results more actionable for administrators and auditors. ... -
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Uncertainty Baselines
High-quality implementations of standard and SOTA methods
Uncertainty Baselines is a collection of strong, well-documented training pipelines that make it straightforward to evaluate predictive uncertainty in modern machine learning models. Rather than offering toy scripts, it provides end-to-end recipes—data input, model architectures, training loops, evaluation metrics, and logging—so results are comparable across runs and research groups. The library spans canonical modalities and tasks, from image classification and NLP to tabular problems, with baselines that cover both deterministic and probabilistic approaches. ... -
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ML for Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
...Each lesson aims to connect the algorithm to a relatable scenario, reinforcing intuition before diving into parameters, metrics, and trade-offs. The repository includes quizzes, solutions, and instructor materials to make the content usable in classrooms or self-study. It emphasizes ethical considerations and model evaluation—accuracy is not the only metric—so students learn to validate and communicate results responsibly. By the end, participants can build end-to-end ML experiments, interpret outputs, and iterate with confidence rather than just copying code. -
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Trafilatura
Python & command-line tool to gather text on the Web
...Going from raw HTML to essential parts can alleviate many problems related to text quality, first by avoiding the noise caused by recurring elements (headers, footers, links/blogroll etc.) and second by including information such as author and date in order to make sense of the data. The extractor tries to strike a balance between limiting noise (precision) and including all valid parts (recall). It also has to be robust and reasonably fast, it runs in production on millions of documents. -
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HelloGitHub
Share interesting, entry-level open source projects on GitHub
...Later, I plan to share these interesting and valuable open source projects with you. I ended up writing this website for easy viewing and sharing. Open source projects in various languages, tools to make life better, books, study notes, tutorials, and more. Through these projects, you will learn more programming knowledge, improve your programming skills, and discover the joy of programming. -
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seq2seq-couplet
Play couplet with seq2seq model
...It also supports serving the trained model through a web service, allowing users to interact with the system after training is complete. In addition to local execution, the project includes Docker files, which make it easier to package and deploy the application in a more reproducible way. The repository also points users to an external dataset source and documents vocabulary formatting requirements for custom datasets, showing that it is meant for both experimentation and extension. -
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Advanced AI explainability for PyTorch
Advanced AI Explainability for computer vision
...The project implements Grad-CAM and several related visualization methods that highlight the regions of an image that most strongly influence a neural network’s decision. These visualization techniques allow developers and researchers to better understand how convolutional neural networks and transformer-based vision models make predictions. The library supports a wide variety of tasks including image classification, object detection, semantic segmentation, and similarity analysis. It also provides metrics and evaluation tools that help measure the reliability and quality of the generated explanations. By integrating easily with PyTorch models, the library allows developers to diagnose model errors, detect biases in datasets, and improve model transparency. -
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TimesFM
Pretrained time-series foundation model developed by Google Research
...It provides a decoder-only model approach to forecasting, aiming for strong performance even in zero-shot or low-data settings where traditional models often struggle. The project includes code and an inference API intended to make it practical to run forecasts programmatically, with options to use different backends such as Torch or Flax depending on your environment and performance needs. Newer releases emphasize expanded context handling and more flexible forecasting outputs, including quantile forecasting so users can get uncertainty estimates rather than only point predictions. ... -
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Double Conversion
Efficient binary-decimal & decimal-binary conversion routines for IEEE
Double Conversion is a high-performance C++ library that provides precise and efficient binary-decimal and decimal-binary conversion routines for IEEE 754 double-precision floating-point numbers. Originally extracted from the V8 JavaScript engine, it was refactored into a standalone library to make its robust number conversion algorithms easily reusable in other projects. The library ensures consistent and accurate results for converting between double values and their string representations, avoiding rounding errors and performance bottlenecks common in standard conversion routines. It is optimized for both speed and correctness, making it ideal for numerical computation libraries, serialization systems, and scripting engines. ... -
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Open X-Embodiment
Unified open dataset enabling cross-embodiment learning for robotics
Open X-Embodiment is a large-scale collaborative initiative led by Google DeepMind to unify robotic learning datasets into a consistent and standardized format, simplifying access and usage across the robotics research community. Its primary goal is to make all available open-source robotic data interoperable by representing them using the RLDS (Reinforcement Learning Dataset Structure) episode format. This enables seamless integration for training, evaluation, and model development across diverse robotic tasks and embodiments. The dataset aggregates contributions from multiple open-source robotic projects, all harmonized under a single unified data schema. ... -
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Penzai
A JAX research toolkit to build, edit, & visualize neural networks
Penzai, developed by Google DeepMind, is a JAX-based library for representing, visualizing, and manipulating neural network models as functional pytree data structures. It is designed to make machine learning research more interpretable and interactive, particularly for tasks like model surgery, ablation studies, architecture debugging, and interpretability research. Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained inspection and modification after training. ... -
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FastVLM
This repository contains the official implementation of FastVLM
...Apple’s research brief frames FastVLM as targeting real-time or latency-sensitive scenarios, where lowering visual token pressure is critical to interactive UX. In short, it’s a practical recipe to make VLMs fast without exotic token-selection heuristics. -
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Purple Llama
Set of tools to assess and improve LLM security
...CyberSecEval, one of its flagship components, provides repeatable evaluations for security risk, including agent-oriented tasks such as automated patching benchmarks. The aim is to make safety practical: ship testable baselines, publish metrics, and provide drop-in implementations that reduce friction for teams adopting Llama. Documentation and sites attached to the repo walk through setup, usage, and the rationale behind each safeguard, encouraging community contributions. -
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Public APIs
A collective list of free APIs
...Curated by community contributors and the team at APILayer, it serves as a centralized resource for discovering APIs across a wide range of domains, including data, machine learning, weather, entertainment, and finance. The project aims to make API exploration and integration more accessible by offering a single, organized index of open and free-to-use APIs. Developers can leverage this list to enhance their products, prototypes, or research projects without the need to build data sources from scratch. The repository’s open nature encourages contributions, allowing anyone to submit new APIs or updates through pull requests. ... -
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Remarkable for Linux
The Markdown Editor for Linux
With Live Preview you can see your changes as you make them. There is no need to export first to check your syntax. This is accompanied by synchronized scrolling. Remarkable has Github Flavoured Markdown. This has a simple, easy-to-learn syntax with features like checklists, highlighting, links, images and more. Remarkable allows you to export your files to PDF and HTML from within the app. -
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amrlib
A python library that makes AMR parsing, generation and visualization
A python library that makes AMR parsing, generation and visualization simple. amrlib is a python module designed to make processing for Abstract Meaning Representation (AMR) simple by providing the following functions. Sentence to Graph (StoG) parsing to create AMR graphs from English sentences. Graph to Sentence (GtoS) generation for turning AMR graphs into English sentences. A QT-based GUI to facilitate the conversion of sentences to graphs and back to sentences. -
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Haiku
JAX-based neural network library
...Haiku is a simple neural network library for JAX that enables users to use familiar object-oriented programming models while allowing full access to JAX’s pure function transformations. Haiku is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used across DeepMind. It preserves Sonnet’s module-based programming model for state management while retaining access to JAX’s function transformations. Haiku can be expected to compose with other libraries and work well with the rest of JAX. ... -
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torchtext
Data loaders and abstractions for text and NLP
...Alternatively, you might want to use the Moses tokenizer port in SacreMoses (split from NLTK). You have to install SacreMoses. To build torchtext from source, you need git, CMake and C++11 compiler such as g++. When building from source, make sure that you have the same C++ compiler as the one used to build PyTorch. A simple way is to build PyTorch from source and use the same environment to build torchtext. If you are using the nightly build of PyTorch, check out the environment it was built with conda (here) and pip (here). Text classification: SST2, AG_NEWS, SogouNews, DBpedia, YelpReviewPolarity, YelpReviewFull, YahooAnswers, AmazonReviewPolarity, AmazonReviewFull, IMDB, etc. -
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TensorFlow Probability
Probabilistic reasoning and statistical analysis in TensorFlow
...TensorFlow Probability (TFP) is a Python library built on TensorFlow that makes it easy to combine probabilistic models and deep learning on modern hardware (TPU, GPU). It's for data scientists, statisticians, ML researchers, and practitioners who want to encode domain knowledge to understand data and make predictions. Since TFP inherits the benefits of TensorFlow, you can build, fit, and deploy a model using a single language throughout the lifecycle of model exploration and production. TFP is open source and available on GitHub. Tools to build deep probabilistic models, including probabilistic layers and a `JointDistribution` abstraction. ... -
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AWS ParallelCluster Node
Python package installed on the Amazon EC2 instances
aws-parallelcluster-node is the python package installed on the Amazon EC2 instances launched as part of AWS ParallelCluster. AWS ParallelCluster is an AWS-supported Open Source cluster management tool that makes it easy for you to deploy and manage High-Performance Computing (HPC) clusters in the AWS cloud. Built on the Open Source CfnCluster project, AWS ParallelCluster enables you to quickly build an HPC compute environment in AWS. It automatically sets up the required compute resources... -
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MicroK8s
Single-package Kubernetes for developers, IoT and edge
...When you lose a cluster database node, another node is promoted. No admin needed for your bulletproof edge. MicroK8s is small, with sensible defaults that ‘just work’. A quick install, easy upgrades and great security make it perfect for micro clouds and edge computing. As the publishers of MicroK8s, we deliver the world’s most efficient multi-cloud, multi-arch Kubernetes. Under the cell tower. On the racecar. On satellites or everyday appliances, MicroK8s delivers the full Kubernetes experience on IoT and micro clouds. Fully containerized deployment with compressed over-the-air updates for ultra-reliable operations. ... -
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Local File Organizer
An AI-powered file management tool that ensures privacy
...It uses language and vision models to understand the contents of documents, images, and other file types so that files can be grouped intelligently according to their meaning or context. The system scans directories, extracts relevant information from files, and restructures folder hierarchies to make content easier to locate and manage. Through AI-driven analysis, the software can detect themes, topics, and metadata in files, allowing it to organize information in ways that traditional rule-based file managers cannot achieve. The tool supports multiple sorting strategies that allow users to categorize files by content, date, or type depending on their workflow preferences. -
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Agentex
Open source codebase for Scale Agentex
...It treats an “agent” as a composition of a policy (the LLM), tools, memory, and an execution runtime so you can test the whole loop, not just prompting. The repo focuses on structured experiments: standardized tasks, canonical tool interfaces, and logs that make it possible to compare models, prompts, and tool sets fairly. It also includes evaluation harnesses that capture success criteria and partial credit, plus traces you can inspect to understand where reasoning or tool use failed. The design encourages clean separation between experiment configuration and code, which makes sharing results or re-running baselines straightforward. ...
