Search Results for "knowledge" - Page 8
Sort By:
Showing 205 open source projects for "knowledge"
View related business solutions-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
1
AI-powered enterprise search engine
AI-powered enterprise search engine
AI-powered enterprise search engine is an open-source, AI-powered enterprise search engine designed to help organizations quickly locate and retrieve information scattered across multiple internal tools, documents, and communication platforms. It enables users to search across sources such as Slack, Confluence, Jira, Google Drive, and other enterprise systems, consolidating fragmented knowledge into a single, unified search experience. By leveraging natural language processing, Gerev allows users to query information in plain English, making it easier to find answers without needing exact keywords or knowing where the data is stored. The platform indexes content from connected systems rather than relying on their native search capabilities, resulting in faster and more relevant results across large datasets. ... -
2
MyWingman
Personal AI Assistant For Windows , Linux
... 🌐 Open websites instantly, letting you access information and resources in a snap. 🔍 Perform quick Google searches and get relevant results without lifting a finger. 📖 Access the vast knowledge of Wikipedia with ease, as Wingman fetches you insightful information. 📸 Capture screenshots effortlessly, allowing you to save and share important moments. 💬 Engage in natural conversations with Wingman, leveraging the power of the Facebook BlenderBot-1B-Distill model to provide engaging and human-like responses. ... -
3
ChatGPT Plugins Collection
An unofficial collection of Plugins for ChatGPT
...The project also serves as a starting point for developers interested in building their own custom plugins, offering inspiration and code samples. With its open structure, it encourages collaboration and knowledge sharing in the growing ecosystem of ChatGPT extensions. -
4
Chameleon LLM
Codes for "Chameleon: Plug-and-Play Compositional Reasoning
Discover Chameleon, our cutting-edge compositional reasoning framework designed to enhance large language models (LLMs) and overcome their inherent limitations, such as outdated information and lack of precise reasoning. By integrating various tools such as vision models, web search engines, Python functions, and rule-based modules, Chameleon delivers more accurate, up-to-date, and precise responses, making it a game-changer in the natural language processing landscape. With GPT-4 at its... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
Simple LLM Finetuner
Simple UI for LLM Model Finetuning
...It allows users to customize pre-trained models using relatively small datasets and modest hardware, making it feasible to experiment with LLM training even on consumer-grade GPUs or cloud environments like Google Colab. The tool includes a web-based interface where users can input datasets, configure training parameters, and run fine-tuning jobs without deep knowledge of machine learning pipelines. It leverages libraries such as Hugging Face PEFT to enable efficient adaptation of models by modifying only a subset of parameters, significantly reducing computational requirements. In addition to training, the platform provides inference capabilities so users can immediately test and evaluate their fine-tuned models within the same environment. -
6
ImageAI
A python library built to empower developers
ImageAI is an easy-to-use Computer Vision Python library that empowers developers to easily integrate state-of-the-art Artificial Intelligence features into their new and existing applications and systems. It is used by thousands of developers, students, researchers, tutors and experts in corporate organizations around the world. You will find features supported, links to official documentation as well as articles on ImageAI. ImageAI is widely used around the world by professionals,... -
7
DiffSinger
Singing Voice Synthesis via Shallow Diffusion Mechanism
...The method introduces a “shallow diffusion” mechanism: instead of diffusing over many steps, generation begins at a shallow step determined adaptively, which leverages prior knowledge learned by a simple mel-spectrogram decoder and speeds up inference. -
8
Pattern
Web mining module for Python, with tools for scraping
...The project integrates multiple capabilities into a single framework that allows developers to collect, process, and analyze textual data from the web. It includes modules for web scraping and crawling that can retrieve information from sources such as social media platforms, search engines, and online knowledge bases. In addition to data mining features, the library offers natural language processing functionality including part-of-speech tagging, sentiment analysis, and n-gram extraction. The framework also includes machine learning algorithms that support classification, clustering, and vector space modeling for text analysis tasks. ... -
9
MuZero General
A commented and documented implementation of MuZero
...MuZero is a model-based reinforcement learning method that combines neural networks with Monte Carlo Tree Search to learn decision-making policies without requiring explicit knowledge of the environment’s dynamics. The repository provides a well-documented and commented implementation designed primarily for educational purposes. It allows researchers and developers to train reinforcement learning agents that can learn to play games such as Atari environments or board games. The framework is modular so that users can easily add new environments by defining the game logic and associated hyperparameters. ... -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
-
10
EasyNLP
EasyNLP: A Comprehensive and Easy-to-use NLP Toolkit
EasyNLP is an easy-to-use NLP development and application toolkit in PyTorch, first released inside Alibaba in 2021. It is built with scalable distributed training strategies and supports a comprehensive suite of NLP algorithms for various NLP applications. EasyNLP integrates knowledge distillation and few-shot learning for landing large pre-trained models, together with various popular multi-modality pre-trained models. It provides a unified framework of model training, inference, and deployment for real-world applications. It has powered more than 10 BUs and more than 20 business scenarios within the Alibaba group. ... -
11
DeepLearning Tutorial
Deep Learning Tutorial, Excellent Articles, Deep Learning Tutorial
DeepLearning is an open-source repository that aggregates tutorials, articles, and educational resources related to deep learning and machine learning. The project is designed as a knowledge collection that helps beginners understand neural networks, deep learning architectures, and fundamental machine learning concepts. It contains curated learning materials covering topics such as feedforward neural networks, activation functions, backpropagation algorithms, optimization methods, and convolutional neural networks. ... -
12
Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing... -
13
Deep Learning Papers Reading Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn
Deep Learning Papers Reading Roadmap is a widely known curated reading plan for deep learning that helps newcomers and practitioners navigate the vast literature in a structured and intentional way. It is built around several guiding principles: moving from outline to detail, from older foundational papers to state-of-the-art work, and from generic to more specialized areas while keeping a focus on impactful contributions. The roadmap organizes papers into categories such as fundamentals,... -
14
Hands-on Unsupervised Learning
Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)
...Unsupervised learning can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover. Author Ankur Patel provides practical knowledge on how to apply unsupervised learning using two simple, production-ready Python frameworks - scikit-learn and TensorFlow. With the hands-on examples and code provided, you will identify difficult-to-find patterns in data. -
15
TextBrewer
A PyTorch-based knowledge distillation toolkit
TextBrewer is a PyTorch-based model distillation toolkit for natural language processing. It includes various distillation techniques from both NLP and CV field and provides an easy-to-use distillation framework, which allows users to quickly experiment with the state-of-the-art distillation methods to compress the model with a relatively small sacrifice in the performance, increasing the inference speed and reducing the memory usage. -
16
StellarGraph
Machine Learning on Graphs
StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can... -
17
PyTorch-BigGraph
Generate embeddings from large-scale graph-structured data
...It shards entities into partitions and buckets edges so that each training pass only touches a small slice of parameters, which drastically reduces peak RAM and enables horizontal scaling across machines. PBG supports multi-relation graphs (knowledge graphs) with relation-specific scoring functions, negative sampling strategies, and typed entities, making it suitable for link prediction and retrieval. Its training loop is built for throughput: asynchronous I/O, memory-mapped tensors, and lock-free updates keep GPUs and CPUs fed even at extreme scale. The toolkit includes evaluation metrics and export tools so learned embeddings can be used in downstream nearest-neighbor search, recommendation, or analytics. ... -
18
MMF
A modular framework for vision & language multimodal research
...MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box. MMF is built on top of PyTorch that brings all of its power in your hands. MMF is not strongly opinionated. So you can use all of your PyTorch knowledge here. MMF is created to be easily extensible and composable. Through our modular design, you can use specific components from MMF that you care about. Our configuration system allows MMF to easily adapt to your needs. -
19
DeepLearn
Implementation of research papers on Deep Learning+ NLP+ CV in Python
Welcome to DeepLearn. This repository contains an implementation of the following research papers on NLP, CV, ML, and deep learning. The required dependencies are mentioned in requirement.txt. I will also use dl-text modules for preparing the datasets. If you haven't use it, please do have a quick look at it. CV, transfer learning, representation learning. -
20
Serenata de Amor
Artificial Intelligence for social control of public administration
Serenata de Amor is an open civic technology project that uses data science and artificial intelligence to promote transparency and accountability in public administration. The project was developed by a community of volunteers associated with Open Knowledge Brasil who believe that open data and technology can help citizens monitor government spending. It focuses on analyzing publicly available datasets related to reimbursements claimed by Brazilian congress members in order to detect suspicious or irregular expenses. Machine learning techniques and data analysis pipelines are used to identify anomalies that may indicate misuse of public funds. ... -
21
PyDaMelo
Python-compatible Data mining elementary objects
An attempt at offering machine learning and data mining algorithms at the finest grain we are able to, easy to combine together through Python scripting to glue together the Lego-like bricks. -
22
ExSTraCS
Extended Supervised Tracking and Classifying System
This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces. ExSTraCS was primarily developed to address problems in epidemiological data mining to identify complex patterns relating predictive attributes in noisy datasets to disease phenotypes of interest. ... -
23
OpenCyc is the open source version of the Cyc(r) technology, the world's largest and most complete general knowledge base and reasoning engine. A new release with even more content, better performance, and improved reliability will be up shortly.
-
24
The SLiCproject is the manuscript map for the original rendition of an information classification system designed with the intention of meeting a standard of scientific ordering of all of human knowledge. The system is designated, "Secular Library Classification." The mind maps downloads are currently in .mm format for Freeplane and Freemind applications. Other media forms are expected pending further development, and distribution necessities. The downloads are not completely open-source. Think of the downloads as being free books, but the contents there of are of copyright. ...
-
25
Both forward-chaining and backward-chaining rules (which may include python code) are compiled into python. Can also automatically assemble python programs out of python functions which are attached to backward-chaining rules. See pyke.sourceforge.ne
