Search Results for "artificial intelligence nlp"
Sort By:
Showing 244 open source projects for "artificial intelligence nlp"
View related business solutions-
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
-
1
Stanza
Stanford NLP Python library for many human languages
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Stanza is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of... -
2
AutoResearchClaw
Autonomous research from idea to paper. Chat an Idea. Get a Paper 🦞
AutoResearchClaw is an open-source framework designed to automatically generate full academic research papers from a single idea or topic. Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. It can automatically generate code for experiments, run... -
3
Reinforcement Learning Course Materials
Lecture notes, tutorial tasks including solutions
Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University. The source code for the entire course material is open and everyone is cordially invited to use it for self-learning (students) or to set up their own course (lecturers). -
4
Project NOMAD
Self-contained, offline survival computer with tools, knowledge, & AI
Project N.O.M.A.D. (Node for Offline Media, Archives, and Data) is a self-contained, offline-first knowledge and education server designed to run on local hardware. It combines AI, educational resources, and critical information tools into a single platform accessible through a web browser. Built as a containerized system managed via Docker, it orchestrates multiple applications through a centralized “Command Center” interface. NOMAD enables users to access offline Wikipedia, AI chat, maps,... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
5
ktrain
ktrain is a Python library that makes deep learning AI more accessible
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. With only a few lines... -
6
Awesome production machine learning
Curated list of awesome open source libraries
This repository contains a curated list of awesome open source libraries that will help you deploy, monitor, version, scale, and secure your production machine learning. Open-source frameworks, tutorials, and articles curated by machine learning professionals. Open-source bias audit toolkits for data scientists, machine learning researchers, and policymakers to audit machine learning models for discrimination and bias, and to make informed and equitable decisions around developing and... -
7
Interpretable machine learning
Book about interpretable machine learning
This book is about interpretable machine learning. Machine learning is being built into many products and processes of our daily lives, yet decisions made by machines don't automatically come with an explanation. An explanation increases the trust in the decision and in the machine learning model. As the programmer of an algorithm you want to know whether you can trust the learned model. Did it learn generalizable features? Or are there some odd artifacts in the training data which the... -
8
Recommenders
Best practices on recommendation systems
The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several... -
9
LLM Course
Course to get into Large Language Models (LLMs)
LLM Course is a hands-on, notebook-driven path for learning how large language models work in practice, from data curation to training, fine-tuning, evaluating, and deploying. It emphasizes reproducible experiments: each step is demonstrated with runnable code, clear dependencies, and references to commonly used open-source models and libraries. Learners get exposure to multiple adaptation strategies—LoRA/QLoRA, instruction fine-tuning, and alignment techniques—so they can choose approaches... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
-
10
PageLM
PageLM is a community driven version of NotebookLM
PageLM is an open-source AI-powered education platform that transforms study materials into interactive learning experiences inspired in part by the NotebookLM style of knowledge interaction. It is built to help students, educators, and researchers turn documents and topics into more engaging forms of study rather than leaving content in static notes or isolated files. The platform includes a broad set of learning tools such as contextual chat, Cornell-style note generation, flashcards,... -
11
JaCoP is a Java Constraint Programming solver. It provides a significant number of (global) constraints to facilitate efficient modeling of combinatorial problems, as well as modular design of search. Documentation is available at project Web site. Please, note that the sources from version 4.0 are only available at GitHub.
-
12
QuizSolver
AI-powered quiz solver for Windows. Free to use, easy to set up.
QuizSolver is a free Windows app that uses AI vision to automatically read and answer quiz questions on your screen. It takes a screenshot, detects the answer buttons, sends the question to an AI model, and clicks the correct answer in seconds. Built-in support for Quizalize and Quipper. A Custom mode is available for other quiz sites, though results may vary. HOW TO SET UP: 1. Download and unzip QuizSolver — no installation needed 2. Get a free API key from Groq at... -
13
Programming Without Coding Technology
Create software using visual programming
PWCT is not a Wizard for creating your application in 1 2 3 steps. PWCT is a general-purpose visual programming language designed for novice and expert programmers. A novice programmer can use PWCT to learn programming concepts like Data Structures, Control Structures and Programming Paradigms. An expert programmer can use PWCT to create any large and complex software. Using PWCT we developed a textual programming language Compiler and Virtual Machine without writing a single line of... -
14
Frevo
Frevo is probably the simplest tool for evolutionary design
FREVO is an open-source framework developed in Java to help engineers and scientists in evolutionary design or optimization tasks. The major feature of FREVO is the componentwise decomposition and separation of the key building blocks for each optimization tasks. We identify these as the problem definition, solution representation and the optimization method. This structure enables the components to be designed separately allowing the user to easily swap and evaluate different configurations... -
15
General Knowledge Machine Project
Intellect Modeling Kit: assisting research, diagnostics, consulting
We humans are bound by intellectual abilities. All knowledge is far beyond power of any person. The only way to apply knowledge is to build machines able to present it human way but not limited by volume. Intellect Modeling Kit (IMK) is intended to build knowledge machines (KM) assisting experts on the steps of activity: * Observation; * Producing propositions based on knowledge; * Elimination of impossible propositions; * Selection and verification of the most appropriate... -
16
D2L.ai
Interactive deep learning book with multi-framework code
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge. This open-source book represents our attempt to make deep learning approachable, teaching you the concepts, the context, and the code. The entire book is drafted in Jupyter notebooks, seamlessly integrating exposition figures, math, and interactive examples with self-contained code. Offers sufficient technical depth to... -
17
Desktop Plagiarism Checker
Free plagiarism software for .NET (Windows 7, 8.1, 10, 11)
...The paraphraser tool allows writers to rephrase their sentences to avoid plagiarism, while the summarizer provides a concise overview of a longer text. The AI detector is an advanced feature that uses artificial intelligence to identify potential instances of plagiarism and provides suggestions for rewording. Additionally, the APA citation generator is a helpful tool for creating accurate and properly formatted citations in the American Psychological Association style, saving writers time and effort in citing their sources correctly. With these tools, writers can ensure the originality and integrity of their work. -
18
StudA
A powerful student assistant program
-
19
DIG
A library for graph deep learning research
The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to... -
20
Translation of Selected text or Clipboard contents powered by Google. HotKeys Paste/Change Text auto translated. View in Balloon/Window the result of translation, besides being sent to the clipboard. Screen Capture of Desktop/Game > OCR > Translated.
-
21
Hello AI World
Guide to deploying deep-learning inference networks
Hello AI World is a great way to start using Jetson and experiencing the power of AI. In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. The tutorial focuses on networks related to computer vision, and includes the use of live cameras. You’ll also get to code your own easy-to-follow recognition program in Python or C++, and train... -
22
DeepMind Educational Resources
DeepMind's repo of educational notebooks for learning AI and research
Educational is an open collection of interactive tutorials created by Google DeepMind to make the fundamentals of machine learning and artificial intelligence accessible to learners of all backgrounds. The repository provides hands-on, beginner-friendly resources that introduce essential AI concepts through Google Colab notebooks, combining intuitive explanations with executable code. The tutorials cover a broad range of topics—from foundational Python programming and data handling to supervised, unsupervised, and reinforcement learning, as well as graph neural networks and scientific reasoning. ... -
23
Biogenesis is an artificial life program that simulates the processes involved in the evolution of organisms. It shows colored segment based organisms that mutate and evolve in a 2D environment. Biogenesis is based on Primordial Life.
-
24
Chalk
All-In-One Digital Teaching Assistant
-
25
Catalyst
Accelerated deep learning R&D
Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make...
