Search Results for "machine learning workloads"
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Showing 80 open source projects for "machine learning workloads"
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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. -
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Project Based Learning
Curated list of project-based tutorials
...The collection spans various domains including web development, game programming, systems programming, and machine learning. By following the projects, learners can strengthen problem-solving skills, gain experience with different technologies, and build portfolios. The repository grows with community contributions, making it a dynamic resource for developers at all levels. -
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Companion notebooks for Deep Learning
Jupyter notebooks for the code samples of the book
Companion notebooks for Deep Learning is a collection of Jupyter notebooks that accompany François Chollet’s deep learning curriculum, providing hands-on implementations of key concepts using practical examples. The project covers a wide range of topics, including neural networks, computer vision, natural language processing, and sequence modeling. Each notebook is structured to combine theoretical explanations with executable code, allowing users to experiment and learn interactively. The... -
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Book4_Power-of-Matrix
Book_4_Matrix Power | The Iris Book: From Addition, Subtraction
...The repository is continuously updated and intended to accompany the broader Visualize-ML learning ecosystem. Overall, it serves as a visually driven mathematical foundation for students preparing for data science and machine learning work. -
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PythonPark
Python open source project "The Road to Self-Study Programming"
PythonPark is a large, curated “learning playground” for Python — essentially a comprehensive self-study meta-repository aimed at helping learners progress in Python programming, data science, machine learning, web scraping, and software engineering practices. It aggregates tutorials, learning guides, project examples, and resources across topics: from Python basics and data structures to machine learning, web scraping, and even interview preparation and “programmer life” guidance. ... -
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Perfect Roadmap To Learn Data Science
Basic To Intermediate Python data science guide
Perfect Roadmap To Learn Data Science In 2025 is an extended, updated learning pathway curated for the modern data-science landscape — blending classical data-analysis, statistics, machine learning, deep learning, computer vision, NLP, as well as current deployment and MLOps practices to prepare learners for data-science careers in 2025. The roadmap is organized to guide learners systematically: starting with Python fundamentals and math/statistics, then progressing through classical machine-learning, deep-learning, data preprocessing, feature engineering, and onto domain-specific applications like computer vision or NLP, ending with deployment, real-world project construction, and best practices for production readiness. ... -
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Fuzzy machine learning framework
A library and a GUI front-end for fuzzy machine learning
Fuzzy machine learning framework is a library and a GUI front-end for machine learning using intuitionistic fuzzy data. The approach is based on the intuitionistic fuzzy sets and the possibility theory. Further characteristics are fuzzy features and classes; numeric, enumeration features and features based on linguistic variables; user-defined features; derived and evaluated features; classifiers as features for building hierarchical systems; automatic refinement in case of dependent features; incremental learning; fuzzy control language support; object-oriented software design with extensible objects and automatic garbage collection; generic data base support through ODBC or SQLite; text I/O and HTML output; an advanced graphical user interface based on GTK+; and examples of use. -
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ML for Beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
ML-For-Beginners is a structured, project-driven curriculum that teaches foundational machine learning concepts with approachable math and lots of code. Organized as a multi-week course, it mixes short lectures with labs in notebooks so learners practice regression, classification, clustering, and recommendation techniques on real datasets. Each lesson aims to connect the algorithm to a relatable scenario, reinforcing intuition before diving into parameters, metrics, and trade-offs. ... -
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freeCodeCamp
freeCodeCamp.org's open-source codebase and curriculum
freeCodeCamp is a nonprofit educational platform that offers a self-paced curriculum for learning web development, programming, data visualization, APIs, and algorithms. It features interactive coding challenges, real-world projects, and guided progress through topic modules, culminating in certificates for completed tracks. A key aspect is that students contribute to open-source projects for nonprofits or internal tooling as part of their learning, reinforcing both technical and... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Book1_Python-For-Beginners
The Iris Book: Addition, Subtraction, Multiplication, and Division
...It integrates visual aids and annotated code examples to help learners understand not just how Python works but why certain patterns are used. The material is structured to support self-paced learning, making it suitable for students, career switchers, and hobbyists. Because the book is part of a larger data science pathway, it also prepares readers for later work in visualization and machine learning. Overall, it serves as an accessible on-ramp into Python within a broader analytical learning journey. -
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Book5_Essentials-Probability-Statistics
The book 5 of statistics in simplicity
Book5_Essentials-of-Probability-and-Statistics is a Visualize-ML educational volume that introduces the statistical and probabilistic concepts underpinning modern data analysis and machine learning. The repository explains topics such as distributions, sampling, inference, and uncertainty using visual demonstrations and intuitive narratives. Its teaching philosophy prioritizes conceptual clarity over heavy formalism, making statistical thinking more approachable for beginners. The material connects probability theory directly to real analytical workflows, helping learners understand how statistics supports predictive modeling. ... -
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Docker-Zero-to-Hero
Repo to learn Docker with examples
...Examples in the examples folder give you hands-on workloads to run so you can see how Docker behaves in real scenarios. The style is beginner-friendly and frequently uses analogies and screenshots to make abstract concepts more relatable, for instance contrasting the size of an Ubuntu container image to a full VM. The repo also links to a full YouTube playlist, so you can learn via video while using the GitHub materials as a companion guide. -
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aie-book
Resources for AI engineers
aie-book is an open-source companion repository that supports a comprehensive guide to building real-world applications with modern AI systems, particularly those based on foundation models. It focuses on bridging the gap between theoretical machine learning knowledge and practical engineering workflows required to deploy AI systems in production. The material emphasizes system design, data pipelines, evaluation strategies, and deployment considerations rather than just model training. It explores how to work with large language models, retrieval systems, and agent-based architectures, providing a practical perspective on how AI is actually used in industry. ... -
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Fanyi
A 🇨🇳 and 🇺🇸 translate tool in your command line
Fanyi is a tool for translating words between the Chinese and English languages, right in your command line. It’s a good supportive tool for learning and reading the Chinese language from English, or the other way around. All translation data is fetched from iciba.com and fanyi.youdao.com, and with each translation comprehensive and related samples are given for better understanding and proper usage. There are translations for words as well as sentences, and in Mac/Linux bash, words can even... -
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eat Pytorch in 20 days
Provides a structured introduction to deep learning development
Eat PyTorch in 20 Days is an open-source educational project that provides a structured introduction to deep learning development with PyTorch. Designed for learners with basic machine learning experience, it organizes tutorials into progressive lessons covering essential concepts and practical workflows. The material explains tensor operations, automatic differentiation, neural network components, and model construction. It demonstrates how to prepare datasets, configure loss functions, manage optimizers, and train models using different approaches. ... -
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AWESOME DATA SCIENCE
Awesome Data Science repository to learn and apply for real world
An open source Data Science repository to learn and apply towards solving real world problems. This is a shortcut path to start studying Data Science. Just follow the steps to answer the questions, "What is Data Science and what should I study to learn Data Science?" Data Science is one of the hottest topics on the Computer and Internet farmland nowadays. People have gathered data from applications and systems until today and now is the time to analyze them. The next steps are producing... -
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AI Engineering Field Guide
Research into AI engineering interview assignments
AI Engineering Field Guide is an open-source, research-based career resource that explains the skills, responsibilities, and hiring expectations associated with AI engineering. It analyzes thousands of real job descriptions to identify commonly requested technologies and professional competencies. The guide compares AI engineering with machine learning, data science, backend development, and related roles. It provides interview preparation materials covering programming, AI system design, language models, retrieval-augmented generation, and autonomous agents. Readers can examine real take-home assignments, technical questions, and company-specific hiring practices. Structured learning paths help professionals transition into AI engineering from different backgrounds. ... -
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Book3_Elements-of-Mathematics
From Addition, Subtraction, Multiplication, and Division to ML
...It is particularly useful for self-taught developers and students transitioning into technical fields that require mathematical literacy. Overall, the project functions as a bridge between basic math education and more specialized machine learning study. -
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Roadmap To Learn Generative AI In 2025
Basic Machine Learning Natural Language Processing Roadmap
Roadmap To Learn Generative AI In 2025 is a curated learning path focused on contemporary generative AI — covering large language models (LLMs), diffusion-based image generation, prompt engineering, multi-modal AI, fine-tuning techniques, and the practical considerations for deploying generative models. It’s aimed at learners and developers who already have some programming or ML basics and wish to specialize in generative AI, offering a modern, structured plan that reflects the state of the... -
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OpenScience
The open-source AI workbench for scientific research
...The project includes research agents, domain specialists, critique agents, literature-review agents, and more than 290 scientific skills. OpenScience is especially useful for machine learning, biology, physics, chemistry, and research automation workflows that need tool use and provenance. -
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Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy
The Complete-Python-3-Bootcamp repository is an educational resource created by Pierian Data as part of their popular Python for Data Science and Machine Learning Bootcamp course. It contains a comprehensive collection of Jupyter Notebooks designed to teach Python programming from the ground up. The repository covers a wide range of Python topics, including data types, control flow, functions, object-oriented programming, error handling, modules, and advanced concepts like decorators and generators. ... -
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Book2_Beauty-of-Data-Visualization
Machine Learning, Criticism and Correction
Book2_Beauty-of-Data-Visualization is an open educational project that teaches the principles and techniques of effective data visualization using Python and modern plotting libraries. The repository focuses on both the technical and aesthetic aspects of visual analytics, helping learners understand how to communicate data clearly and persuasively. It includes practical examples that demonstrate how different chart types reveal patterns, trends, and distributions in real datasets. The... -
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Best-of Python
A ranked list of awesome Python open-source libraries
This curated list contains 390 awesome open-source projects with a total of 1.4M stars grouped into 28 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome! Ranked list of awesome python libraries for web... -
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Safe Exam Browser is a webbrowser-environment to carry out online-exams safely. The software changes any computer into a secure workstation. It regulates the access to any utilities and prevents students from using unauthorised resources.
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The Grand Complete Data Science Guide
Data Science Guide With Videos And Materials
The Grand Complete Data Science Materials is a repository curated by a data-science educator that aggregates a wide range of learning resources — from basic programming and math foundation to advanced topics in machine learning, deep learning, natural language processing, computer vision, and deployment practices — into a structured, centralized collection aimed at learners seeking a comprehensive path to data science mastery. The repository bundles tutorials, lecture notes, project outlines, course materials, and references across topics like Python, statistics, ML algorithms, deep learning, NLP, data preprocessing, model evaluation, and real-world problem solving. ...
