Search Results for "knowledge" - Page 11
Sort By:
Showing 381 open source projects for "knowledge"
View related business solutions-
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.
-
$300 Free Credits to Build on Google CloudStart your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
-
1
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... -
2
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,... -
3
SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple computational steps, while maintaining speaker consistency across output channels. Separate models are trained for different speaker counts, and the largest-capacity model dynamically determines the actual number of speakers in a mixture. ... -
4
YOLOR
implementation of paper - You Only Learn One Representation
...Its central contribution is the use of implicit knowledge to improve network performance without treating every task as fully separate. It is useful for computer vision researchers and developers studying YOLO-style detectors, representation learning, and high-performance detection systems. -
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.
-
5
Menu Maker is 100% Python heuristics-driven menu generator for a number of X Window Managers and desktop environments. It features large knowledge base of known programs, powerful and flexible search algorithms, persistence of menus across several WMs
-
6
EduData
Datasets in Education and convenient interface for dataset
...Each item in the sequence represents one interaction. The first element of the item is the exercise id (in some works, the exercise id is not one-to-one mapped to one knowledge unit(ku)/concept, but in junyi, one exercise contains one ku) and the second one indicates whether the learner correctly answers the exercise, 0 for wrongly while 1 for correctly. -
7
workshops_project
Workshops is an open source, simple, dead-lightweight LMS
Workshops is an open source, simple, dead-lightweight LMS (Learning Management System) application programmed in Python (version 3.8.x) with Django (version 2.2.x) web framework which main purpose is to make a standarized way to share knowledge via courses in a slide-based view in browser powered by remark javascript library, easy to create, edit, delete and show your courses using simple markdown and html if necessary. Inspired on an old project in my social labours to help share knowledge in an easy way. -
8
...(I watch YouTube, I know you guys are out there...) This is not a beginner project, it involves multiple pieces of equipment and various expertise. Proceed at own risk. Working knowledge of Linux and Windows computers required. This is not a tutorial on how to use your computers. Still here? Awesome! This setup works with a connected PC. You can watch movies and play games with the backglow running. Adds extra ambience to your expeirence. Especially as you transition from bright outdoor scenes to darker indoors ones.
-
9
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. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
10
instagram-spammer
instagram spammer, spam, spammer, spambot, spammerbot, pythonspam
...If you DON'T KNOW how to use this script please read README.TXT file. WARNING This script contains packages that may NEED to be installed using PIP. Use this script only with basic programming/python knowledge. -
11
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. -
12
FusionCatcher
Somatic fusion-genes finder for RNA-seq data
FusionCatcher searches for novel/known somatic fusion genes, translocations, and chimeras in RNA-seq data (paired-end reads from Illumina NGS platforms like Solexa and HiSeq) from diseased samples. The aims of FusionCatcher are: - very good detection rate for finding candidate fusion genes, - very easy to use (i.e. no a priori knowledge of databases and bioinformatics is needed in order to run FusionCatcher), - very good detection of challenging fusion genes, like for example IGH fusions, CIC fusions, DUX4 fusions, CRLF2 fusions, TCF3 fusions, etc. - to be as automatic as possible (i.e. the FusionCatcher will choose automatically the best parameters in order to find candidate fusion genes, e.g. finding automatically the adapters, building the exon-exon junctions automatically based on the length of the input reads, etc.) while providing the best possible detection rate for finding fusion genes. -
13
Pytholog
A logic programming tool and a logical database with a RESTful API
...Let's look at the arguments that can be specified while initiating the tool: $ ./Pytholog -h usage: Pytholog [-h] [-c CONSULT] -n NAME [-i] [-a] pytholog executable tool: prolog experience at command line and a logic knowledge base with no dependencies optional arguments: -h, --help show this help message and exit -c CONSULT, --consult CONSULT read an existing prolog file/knowledge base -n NAME, --name NAME knowledge base name -i, --interactive start an interactive prolog-like session -a, --api start a flask api -
14
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... -
15
Streisand
Streisand sets up a new server running your choice
...It was created to help users bypass internet censorship and surveillance by quickly setting up secure communication channels without needing deep system administration expertise. With just a cloud provider account and basic Unix command-line knowledge, Streisand can provision a server and configure multiple VPN and proxy protocols almost automatically. This includes OpenVPN, WireGuard, Shadowsocks, OpenConnect, and Tor bridges, often with optional add-ons like obfuscation or stunnel to resist throttling and detection. The result is a private website that hosts client software downloads and setup instructions for easy access. ... -
16
Retro
Retro Games in Gym
...Instead of relying solely on learned parameters, RETRO retrieves relevant documents from a large external database during inference, allowing it to ground responses in external knowledge. This design improves factual accuracy, reduces hallucinations, and enables smaller models to perform comparably to much larger ones by leveraging retrieval. The repository provides code and resources for training and evaluating RETRO models, along with infrastructure for integrating retrieval into the transformer pipeline. It includes example configurations, datasets, and utilities for building retrieval-augmented generation systems. ... -
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
BotSlayer
BotSlayer Community Edition
...BotSlayer can be used, for example, by journalists, corporations, and political candidates to discover in real-time new coordinated campaigns in their domains of interest, without any prior knowledge of these campaigns. The system is easily installed and configured in the cloud to monitor bot activity around a standing user-defined query. All you need is a Twitter developer app key to fetch data from the Twitter streaming API. -
19
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. -
20
Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
-
21
Game Programmer
A Study Path for Game Programmer
...The project is useful for self-taught developers who need a long-term curriculum and a way to identify gaps in their knowledge. Its main value is organizing a complex discipline into a visual, staged study map. -
22
CrimeKgAssitant
Crime assistant including crime type prediction
CrimeKgAssitant is a Chinese-language legal NLP project that combines offense prediction, consultation classification, automated answers, and knowledge graph queries. It organizes data around criminal charges, sentencing cases, legal question-and-answer pairs, and related legal information. A multiclass model predicts likely offense categories from written case descriptions using document embeddings and a support vector machine. Separate classifiers sort consultation questions into predefined legal categories before retrieving or generating relevant responses from the prepared knowledge base. ... -
23
pybotlib
Python Robotic Process Automation Library
...Check out the API Documentation for more details. The project is centered around open technologies and the believe that the future of digital transformation across business is rooted in a shared knowledge economy. -
24
ComplexEventExtraction
Expression pattern collection of Chinese compound event extraction
...It also discusses several event representations, including clauses, token sequences, and syntactic phrases. The project is intended as a research reference for event extraction, knowledge modeling, forecasting, and language-resource development. -
25
Teach Me Quantum
Practical Course on Quantum Information Science and Quantum Computing
A university-level course on Quantum Computing and Quantum Information Science that incorporates IBM Q Experience and Qiskit. This course is adequate for general audiences without prior knowledge on Quantum Mechanics and Quantum Computing (see prior knowledge), has an estimated average duration of 10 weeks at 3h/week (see duration), and is meant to be the entrypoint into the Quantum World.
