Search Results for "tutorials"
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Showing 652 open source projects for "tutorials"
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Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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Machine Learning Tutorials Repository
Dive deep into the realms of Machine Learning and other topics
The Machine Learning Tutorials Repository is a comprehensive collection of resources, examples, and implementations designed to help users understand and apply machine learning concepts. It covers a wide range of topics, including supervised learning, unsupervised learning, neural networks, and data preprocessing techniques. The project is structured to provide both theoretical explanations and practical code examples, making it suitable for learners at different levels. -
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Java and Spring Tutorials
Getting Started with Spring Boot 3
Java and Spring Tutorials is a large-scale educational codebase that provides practical examples and tutorials covering a wide range of software development topics, primarily focused on Java and related ecosystems. It serves as a companion resource for Baeldung articles, offering real-world code implementations that demonstrate concepts such as Spring Boot, persistence frameworks, REST APIs, security, testing, and more. -
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Python Code Tutorials
The Python Code Tutorials
Python Code Tutorials is a large educational repository that aggregates programming tutorials from the “The Python Code” website into a structured collection of Python projects and learning materials. The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. -
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machine learning tutorials
machine learning tutorials (mainly in Python3)
machine-learning is a continuously updated repository documenting the author’s learning journey through data science and machine learning topics using practical tutorials and experiments. The project presents educational notebooks that combine mathematical explanations with code implementations using Python’s scientific computing ecosystem. Topics covered include classical machine learning algorithms, deep learning models, reinforcement learning, model deployment, and time-series analysis. The repository integrates numerous popular machine learning frameworks and libraries such as scikit-learn, PyTorch, TensorFlow, XGBoost, and Hugging Face. ... -
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.
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AI-Tutorials/Implementations Notebooks
Codes/Notebooks for AI Projects
AI-Tutorials/Implementations Notebooks repository is a comprehensive collection of artificial intelligence tutorials and implementation examples intended for developers, students, and researchers who want to learn by building practical AI projects. The repository contains numerous Jupyter notebooks and code samples that demonstrate modern techniques in machine learning, deep learning, data science, and large language model workflows. -
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pytorch-cpp
C++ Implementation of PyTorch Tutorials for Everyone
...Requires installed python3 with PyTorch and torch-vision. You can choose to only build tutorials in one of the categories basics, intermediate, advanced or popular. You can build and run the tutorials (on CPU) in a Docker container using the provided Dockerfile and docker-compose.yml files. -
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Agents Towards Production
Code-first tutorials covering every layer of GenAI agents
...Instead of focusing only on toy examples, it dives into every layer of an agent stack: orchestration, memory, RAG, tool and API integration, security, observability, deployment, evaluation, and UI. The repository is built around runnable tutorials, each in its own folder, often sponsored by or built in collaboration with infrastructure providers like LangChain, Redis, Bright Data, Contextual AI, Tavily, Runpod, Portia, and others. These tutorials show how to implement things like secure tool calling with OAuth, dual-memory architectures, production RAG agents, multi-agent communication protocols, GPU deployment, containerization with Docker, FastAPI endpoints, and Streamlit chat UIs. ... -
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ProjectLearn.io
A curated list of project tutorials for project-based learning
ProjectLearn.io is an open-source repository that aggregates curated tutorials focused on project-based programming education. The project organizes learning resources where users build complete applications from scratch, helping learners acquire practical development experience rather than relying solely on theoretical tutorials. The repository includes projects across multiple domains such as web development, mobile development, machine learning, artificial intelligence, and game development. ... -
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OpenVINO Notebooks
Jupyter notebook tutorials for OpenVINO
openvino_notebooks is a collection of interactive Jupyter notebooks designed to demonstrate how to build, optimize, and deploy artificial intelligence applications using the OpenVINO toolkit. The repository provides practical tutorials that guide developers through various AI workflows including computer vision, natural language processing, and generative AI tasks. Each notebook demonstrates how to run pre-trained models, optimize inference performance, and deploy models across hardware such as CPUs, GPUs, and specialized accelerators. The tutorials also illustrate how OpenVINO integrates with models from frameworks like PyTorch, TensorFlow, and ONNX to accelerate inference workloads. ... -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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MongoDB JVM Driver
The MongoDB drivers for Java, Kotlin, and Scala
Welcome to the documentation site for the Java Driver, the MongoDB driver for synchronous Java applications. Download it using Maven or Gradle, or set up a runnable project by following our Quick Start guide. For tutorials on how to use the MongoDB JVM Drivers, please reference MongoDB University. Additional tutorials, videos, and code examples using both the Java Driver and the Kotlin Driver can also be found in the MongoDB Developer Center. -
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ai-cookbook
Examples and tutorials to help developers build AI systems
...Developers can learn how to construct applications like intelligent assistants, automation pipelines, and AI-powered data analysis tools through step-by-step tutorials and ready-to-run scripts. The code examples are designed to emphasize practical architecture patterns that are commonly used in production environments, helping developers understand how to integrate AI services into software products. -
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Build your own X
Master programming by recreating your favorite technologies
...Categories include everything from graphics and cryptography to search engines and version control, making it a practical jumping-off point for portfolio pieces or study projects. Because most items are self-contained tutorials or repositories, you can progress incrementally and switch topics without losing momentum. -
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Cookbook (Google Gemini)
Examples and guides for using the Gemini API
...The Cookbook also includes tutorials on advanced API workflows such as grounding answers with external tools, batch-mode request handling, and live multimodal interactivity with LiveAPI. Designed as a hands-on resource, it helps developers quickly explore Gemini’s potential while serving as a reference for integrating cutting-edge multimodal AI into applications. -
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LLM-Finetuning
LLM Finetuning with peft
...The repository includes step-by-step notebooks demonstrating how to fine-tune models such as LLaMA, Falcon, OPT, Vicuna, and GPT-NeoX. These tutorials show how developers can adapt pretrained models for tasks such as chatbots, classification, and instruction following. The project also illustrates how low-precision training techniques and adapter-based methods reduce memory requirements while maintaining strong model performance. -
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Awesome-FL
Comprehensive and timely academic information on federated learning
A “awesome” curated list of federated learning (FL) academic resources: research papers, tools, frameworks, datasets, tutorials, and workshops. A hub for FL knowledge maintained by the academic community. -
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Lean 4
Lean 4 programming language and theorem prover
...One of its defining characteristics is its emphasis on extensibility, since Lean 4 is built to allow users to develop custom automation, metaprogramming tools, and domain-specific extensions instead of being limited to a fixed proving workflow. The broader Lean ecosystem also includes official tutorials, language references, examples, and installation and build tools, which reflects that the project is not just a core compiler repository but the center of a mature development platform. -
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Prompt Engineering Techniques
Collection of tutorials for Prompt Engineering techniques
...It contains around twenty-plus hands-on Jupyter notebooks, each dedicated to a specific technique such as basic prompt structures, prompt templates and variables, zero-shot prompting, few-shot prompting, chain-of-thought, self-consistency, constrained generation, role prompting, task decomposition, and more. The tutorials are designed to be practical; you can run them directly, examine the prompts, and see how small changes affect model behavior and quality. The repository is framed as a “techniques library” that complements a more detailed book, which expands on the same topics with deeper explanations and exercises. It is intended for a wide audience, from beginners learning how to structure their first prompts to advanced practitioners optimizing stability, controllability, and reliability in production systems. -
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Data Science Articles from CodeCut
Collection of useful data science topics along with articles
The Data-science repository from CodeCutTech is a curated collection of educational content focused on practical tools and workflows used in modern data science projects. Instead of providing a single software package, the repository aggregates articles, tutorials, and examples covering many topics within the data science ecosystem. The materials address areas such as MLOps, data management, project organization, testing practices, visualization techniques, and productivity tools used by data scientists. Each topic often includes references to code repositories, demonstrations, and video tutorials that show how the tools can be applied in real projects. ... -
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machine_learning_examples
A collection of machine learning examples and tutorials
...Many of the examples are accompanied by tutorials and educational materials that explain how the algorithms work and how they can be applied in real-world projects. The code is organized into small independent experiments so that learners can explore specific algorithms or techniques without needing to understand the entire codebase. -
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The Magic of CSS
A CSS course to turn you into a magician
...It is structured as a series of chapters that cover topics like the box model, layouts, positioning, typography, and animations. The repository is designed to go beyond basic CSS tutorials, teaching how to harness the language for complex, responsive, and visually appealing designs. Each lesson is supported by examples and code that demonstrate real-world use cases. The project emphasizes both the technical and creative potential of CSS, showing how small details can greatly improve user experience. It has become a valuable reference for developers aiming to deepen their front-end skills. -
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MDN Learning Area
GitHub repo for the MDN Learning Area
learning-area is the official GitHub repository for the MDN Web Docs Learning Area, a collection of educational resources designed to teach core web development technologies. It contains the code examples referenced throughout MDN’s tutorials and articles, covering topics such as HTML, CSS, JavaScript, and web APIs. Each directory in the repository mirrors the module structure of the MDN Learning Area, allowing learners to follow along easily as they read through corresponding lessons. The examples are written to be simple, instructive, and directly aligned with MDN’s documentation, making it an ideal hands-on companion for web development education. ... -
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NLP-Knowledge-Graph
Research and application of technologies such as nl processing
...By combining NLP techniques with graph-based data models, knowledge graphs allow systems to represent complex relationships between entities and improve tasks such as question answering, information retrieval, and recommendation systems. The repository aggregates research papers, technical articles, tutorials, and open-source tools related to these areas. -
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Digoal Blog
Opensource, Database, AI, Business
Digoal Blog is a comprehensive collection of articles, tutorials, and resources focused on open-source databases, particularly PostgreSQL. Maintained by Digoal Zhou, the blog covers a wide range of topics including database optimization, architecture, and best practices, serving as a valuable resource for database administrators and developers. -
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Milvus Bootcamp
Dealing with all unstructured data, such as reverse image search
Milvus Bootcamp is a collection of tutorials, examples, and best practices for using Milvus, an open-source vector database designed for AI-powered similarity search and retrieval applications. -
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PyQuil
A Python library for quantum programming using Quil
...However, you can also keep reading below to get started with running your first quantum program. Without installing anything, you can quickly get started with quantum programming by exploring our interactive Jupyter Notebook tutorials and examples. To run them in a preconfigured execution environment on Binder, click the "launch binder" badge at the top of the README or the link here! To learn more about the tutorials and how you can add your own, visit the rigetti/forest-tutorials repository. If you'd rather set everything up locally, or are interested in contributing to pyQuil, continue to the next section for instructions on installing pyQuil and the Forest SDK.
