Search Results for "cdm-core" - Page 13
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Showing 466 open source projects for "cdm-core"
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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.
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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.
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Ungoogled Chromium Android
Android build for ungoogled-chromium
...The goal is to offer an Android browser that feels familiar in capability and rendering fidelity but does not phone home, engage with proprietary APIs, or leak usage data to third-party providers. Because Android’s ecosystem is heavily tied to Google’s app services, this effort focuses on ensuring core browsing functionality, tab management, extension support (as available), and performance optimizations. -
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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,... -
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BPYTOP
Linux/OSX/FreeBSD resource monitor
...The tool is highly configurable through both an in-app options menu and a detailed configuration file, allowing customization of themes, update frequency, graph types, temperature sensors, and which “boxes” (CPU, memory, network, processes) are shown. It supports temperature monitoring, per-core stats, I/O graphs, swap, battery information, and network auto-scaling, making it suitable for serious monitoring on laptops and servers alike. -
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Mycroft
Mycroft Core, the Mycroft Artificial Intelligence platform
Mycroft is the world’s leading open source voice assistant. It is private by default and completely customizable. Our software runs on many platforms, on desktop, our reference hardware, a Raspberry Pi, or your own custom hardware. Our open-source, modular system can be ported to your device or environment, at any price point. Whether you make voice-assistants, televisions, or microwaves. Whether you have a 5-room BnB or a 1000-room hotel. Your customers will get access to all the... -
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
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OpenEMM e-mail & marketing automation
software for email automation (newsletters, transaction mails, etc.)
...OpenEMM offers tons of features for professional users, among them: a great user interface, template-based HTML mailings, automatic bounce management, mail opening and link tracking, lots of graphical realtime statistics, a content management system, self-defined and behaviour-based target groups, a multi-queue mail backend for maximum sending performance, a time-driven automated data import and export feature, an extensive set of webservices, a plugin interface to easily extend the core functionality, a scripting feature to enhance the functionality of OpenEMM with triggerable customized actions and an audit-proof user activity log. -
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...This formalism is an extension of the Shlaer–Mellor method and executable UML, facilitating deployment of domains across multiple hosts, using networked bridges to process and pass events between them. Core technologies: XML, Python, Qt/PySide. Current release solely targets Linux, but has previously run on macOS. Currently released components are: - eda-model: XML schema and schematron that define the storage of a valid design. - eda-model-interface: python3 library for loading, editing, diffing and validating an instance of an EDA design...
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TorchGAN
Research Framework for easy and efficient training of GANs
The torchgan package consists of various generative adversarial networks and utilities that have been found useful in training them. This package provides an easy-to-use API which can be used to train popular GANs as well as develop newer variants. The core idea behind this project is to facilitate easy and rapid generative adversarial model research. TorchGAN is a Pytorch-based framework for designing and developing Generative Adversarial Networks. This framework has been designed to provide building blocks for popular GANs and also to allow customization for cutting-edge research. ... -
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Thesa
It is a Platform to connect to tryton (json-rpc) and is based on qt
Thesa It is a Platform to connect to tryton (json-rpc) and is based on qt/qml libraries. Requires designing the interface of each Tab without having to touch the core. Tabs are created with qml files and can be loaded locally from a folder or from trytond using thesamodule (https://github.com/numaelis/thesamodule). Thesa's goal is to be able to combine tryton with Qt / Qml, for special cases such as using the opengl performance of qml2 Requirements: pyside2 5.12 or higher: https://download.qt.io/official_releases/QtForPython/pyside2/ Run: python3 main.py you can find source code in: https://github.com/numaelis/thesa -
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python-tutorial
Practical Python tutorials, including Python basics
...Its examples are tested in a Python 3 environment and organized into topic-based directories. The repository also includes notebook-style learning materials for basic data types and core language concepts. It is useful as a structured self-study resource, classroom supplement, or quick reference for practical Python usage. -
Demo Series - Small Business Backup By VeeamWatch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
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Deep-Learning-with-TensorFlow-book
Open source Deep Learning book, based on TensorFlow
...It combines theory with practical examples, making it suitable for beginners who want to learn deep learning through hands-on code. The repository includes the PDF book, companion source code, course slides, and notebook-style materials. It covers core machine learning and deep learning concepts through TensorFlow-based implementation. The project also supports educational use, with materials that can be adopted by students, self-learners, and instructors. Overall, it is a complete learning package for understanding modern deep learning workflows through TensorFlow 2.0 examples. -
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Practice Python
Part of my daily plan for studying Python
practice-python provides a structured set of small, focused exercises aimed at building fluency with Python fundamentals. The tasks emphasize real coding over passive reading, nudging you to write, run, and iterate on solutions. Exercises commonly target strings, lists, dictionaries, control flow, functions, classes, and common algorithms, reinforcing idiomatic Python patterns. Many problems are intentionally minimal in boilerplate so you can concentrate on logic and clarity. The collection... -
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Ciphey
Decrypt encryptions without knowing the key or cipher
Fully automated decryption/decoding/cracking tool using natural language processing & artificial intelligence, along with some common sense. You don't know, you just know it's possibly encrypted. Ciphey will figure it out for you. Ciphey can solve most things in 3 seconds or less. Ciphey aims to be a tool to automate a lot of decryptions & decodings such as multiple base encodings, classical ciphers, hashes or more advanced cryptography. If you don't know much about cryptography, or you want... -
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Pytorch Points 3D
Pytorch framework for doing deep learning on point clouds
...We aim to build a tool that can be used for benchmarking SOTA models, while also allowing practitioners to efficiently pursue research into point cloud analysis, with the end goal of building models which can be applied to real-life applications. Task driven implementation with dynamic model and dataset resolution from arguments. Core implementation of common components for point cloud deep learning - greatly simplifying the creation of new models. 4 Base Convolution base classes to simplify the implementation of new convolutions. Each base class supports a different data format. -
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Nautilus Core
Automation tools for deploying blockchain networks
Naultilus Core is a tool to automate running Tezos Nodes. It allows customization of the most important node features, and easily running multiple nodes, along with different integrations to simplfy node interactions. With each Node in Archive mode, you can also start an instance of Conseil and Arronax. Nautilus Core is only supported in macOS and Linux. -
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Bitcoin Black Core
BLACK use peer-to-peer technology to operate with no central authority
...As a permissionless, decentralized cryptocurrency, Bitcoin Black Core requires no trusted third parties and no central bank. Unlike traditional fiat money, Bitcoin Black Core does not depend on monetary middlemen such as banks and payment processors. Transactions cannot be censored by governments or other centralized corporations. Similarly, funds cannot be seized or frozen — because financial third parties have no control over the Bitcoin Black Core network. ... -
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PaddlePaddle models
Pre-trained and Reproduced Deep Learning Models
Pre-trained and Reproduced Deep Learning Models ("Flying Paddle" official model library, including a variety of academic frontier and industrial scene verification of deep learning models) Flying Paddle's industrial-level model library includes a large number of mainstream models that have been polished by industrial practice for a long time and models that have won championships in international competitions; it provides many scenarios for semantic understanding, image classification,... -
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algo
50 Code Implementations You Must Know About Data Structures
algo is an educational repository containing practical implementations of essential data structures and algorithms. It organizes roughly fifty core exercises by topic rather than presenting a single reusable software library. The material covers arrays, linked lists, stacks, queues, recursion, sorting, binary search, hash tables, strings, trees, heaps, and graphs. More advanced examples address backtracking, divide-and-conquer methods, dynamic programming, shortest paths, topological sorting, caches, and priority queues. ... -
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Libra
Ergonomic machine learning for everyone
An ergonomic machine learning library for non-technical users. Save time. Blaze through ML. -
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AWS IoT Greengrass Core SDK
SDK to use with functions running on Greengrass Core using Python
The AWS IoT Greengrass Core SDK is meant to be used by AWS Lambda functions running on an AWS IoT Greengrass Core. It will enable Lambda functions to invoke other Lambda functions deployed to the Greengrass Core, publish messages to the Greengrass Core and work with the local Shadow service. To use the AWS IoT Greengrass Core SDK, you must first import the AWS IoT Greengrass Core SDK in your Lambda function as you would with any other external libraries. ... -
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NLP Architect
A model library for exploring state-of-the-art deep learning
NLP Architect is an open-source Python library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing and Natural Language Understanding neural networks. The library includes our past and ongoing NLP research and development efforts as part of Intel AI Lab. NLP Architect is designed to be flexible for adding new models, neural network components, data handling methods, and for easy training and running models. NLP Architect is a... -
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SageMaker MXNet Training Toolkit
Toolkit for running MXNet training scripts on SageMaker
...With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. You can also train and deploy models with Amazon algorithms, which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training. If you have your own algorithms built into SageMaker compatible Docker containers, you can train and host models using these as well. -
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LiVES
LiVES is a Video Editing System. It is designed to be simple to use, y
LiVES mixes realtime video performance and non-linear editing in one professional quality application. It is designed to be simple to use, yet powerful. It is small in size, yet it has many advanced features. Using LiVES, you can start editing and making video right away, without having to worry about formats, frame sizes, or framerates. It is a very flexible tool which is used by both professional VJ's and video editors - mix and switch clips from the keyboard, use dozens of realtime... -
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interactive-coding-challenges
120+ interactive Python coding interview challenges
Interactive Coding Challenges is a collection of practice problems designed to strengthen data structures, algorithms, and problem-solving skills. The repository emphasizes a learn-by-doing approach: you read a prompt, attempt a solution, and verify behavior with tests, often within notebooks or scripts. Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference... -
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EasyArch
Arch Linux Installer ISO
A simple yet full featured Archlinux installer ISO. Minimum system requirements- Processor - 2 core 64 bit Ram - 1 GB HDD space - 10 GB If you are looking for another linux distro, then you are at wrong place, this is not a new or separate distribution. It is just a live ISO to provide simple and easy way to get Archlinux up and running in very little time and with or without internet connection. Yes, you read it right, you can install Archlinux without internet with this ISO. ... -
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pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
...It is designed primarily for beginners and intermediate practitioners who want to understand PyTorch fundamentals and quickly move toward building real neural network models. The repository walks users through core concepts such as tensors, autograd, neural network modules, convolutional networks, recurrent networks, and transfer learning. Each section includes runnable code examples that progressively increase in complexity, helping learners build intuition while practicing hands-on implementation. Because the tutorials are concise and practical, the project is widely used in classrooms and self-study environments. ...