Search Results for "machine learning python" - Page 2
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135 projects for "machine learning python" with 2 filters applied:
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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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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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Earth Engine API
Python and JavaScript bindings for calling the Earth Engine API
The Earth Engine API provides Python and JavaScript client libraries for Google Earth Engine, a planetary-scale geospatial analysis platform. With it, users compose lazy, server-side computations over massive catalogs of satellite imagery and vector datasets without handling raw files locally. The API exposes functional operators for map algebra, reducers, joins, and machine learning that scale transparently on Earth Engine’s backend. -
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Flama
Fire up your models with the flame
Flama is a python library which establishes a standard framework for development and deployment of APIs with special focus on machine learning (ML). The main aim of the framework is to make ridiculously simple the deployment of ML APIs, simplifying (when possible) the entire process to a single line of code. The library builds on Starlette, and provides an easy-to-learn philosophy to speed up the building of highly performant GraphQL, REST and ML APIs. -
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A to Z Resources for Students
Curated list of resources for developers
A to Z Resources for Students is a curated directory of learning materials, developer tools, programs, events, and career opportunities for students and early-career technologists. It helps users discover resources for learning programming languages, frameworks, AI, machine learning, cybersecurity, mobile development, and other technical fields. The collection also includes hackathons, competitions, internships, student programs, open-source opportunities, and networking communities. ... -
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Interview_Question_for_Beginner
Technical-Interview guidelines written for studying programming
...Core topics include data structures, networking, operating systems, databases, design patterns, algorithms, and general development concepts. Language-specific material covers Java, JavaScript, and Python. Separate sections address frontend development, iOS, and machine learning. The repository also collects real interview questions, reverse-interview suggestions for candidates, learning references, and community contributions through issues and pull requests. -
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.
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learn_python3_spider
Python crawler tutorial series, learning Python crawlers from 0 to 1
learn_python3_spider is a tutorial and example-code collection for learning web scraping with Python 3 from beginner to advanced topics. It introduces request capture, browser and mobile traffic inspection, and core scraping libraries such as Requests, BeautifulSoup, Selenium, Appium, and Scrapy. Lessons also cover JSON parsing, regular expressions, concurrency, proxy usage, login handling, and CAPTCHA-related techniques. -
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ModernGL
Modern OpenGL binding for Python
ModernGL is a Python wrapper over OpenGL, designed to simplify the creation of high-performance, modern graphics applications. It provides an intuitive API for rendering 2D and 3D graphics, making it accessible to both beginners and experienced developers. ModernGL is suitable for applications such as games, simulations, and data visualizations. -
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pytudes
Python programs, usually short, of considerable difficulty
...It is useful for programmers who want to study elegant Python code while learning how experienced developers approach problem solving. Many examples emphasize clarity and compactness rather than framework-heavy engineering. pytudes is best understood as a learning library, a coding style reference, and a set of practical programming studies. -
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HackTheBox CTF Writeups
This cheasheet is aimed at the CTF Players and Beginners
...It serves as a searchable learning index rather than hosting an automated Hack The Box client or exploitation framework. -
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Claude Cookbooks
A collection of notebooks/recipes showcasing ways of using Claude
...The content is organized into thematic sections, allowing users to explore specific capabilities or integration patterns systematically. Designed with accessibility in mind, the examples are primarily written in Python but can be adapted to other languages. -
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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Claude Code Projects Index
An index of my Claude Code related repos
Claude Code Projects Index is a curated directory of projects, tools, and resources built around Claude Code and related AI development ecosystems. It functions as a centralized index that helps developers discover useful repositories, workflows, and integrations. The project is organized to make navigation easy, grouping resources by categories such as tooling, frameworks, and use cases. It is particularly valuable for developers exploring the Claude ecosystem and looking for inspiration or... -
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101 FastAPI Tips
FastAPI Tips by The FastAPI Expert!
...Many entries explain not just what to do, but why a certain pattern is better in FastAPI or Starlette-based applications. The repository is best used as a checklist, reference, and learning guide for building cleaner Python APIs. -
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Recursive Language Models
General plug-and-play inference library for Recursive Language Models
RLM (short for Reinforcement Learning Models) is a modular framework that makes it easier to build, train, evaluate, and deploy reinforcement learning (RL) agents across a wide range of environments and tasks. It provides a consistent API that abstracts away many of the repetitive engineering patterns in RL research and application work, letting developers focus on modeling, experimentation, and fine-tuning rather than infrastructure plumbing. Within the framework, you can define custom... -
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YOLOv9
Learning What You Want to Learn Using Programmable Gradient Info
YOLOv9 is the official implementation of the paper “YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information.” It is a modern object detection repository focused on improving how deep networks preserve useful information during training. The project introduces Programmable Gradient Information and the GELAN architecture to improve gradient flow, parameter efficiency, and train-from-scratch performance. It provides scripts and model assets for training, testing, and... -
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Jupyter Docker Stacks
Ready-to-run Docker images containing Jupyter applications
Jupyter Docker Stacks provides a curated set of ready-to-run Docker container images that bundle Jupyter applications with popular data science and computing tools, enabling users to quickly start working in a reproducible environment. These stacks support a range of use cases, from lightweight base notebook images to full featured environments that include scientific computing libraries, machine learning tools, and IDE-like notebook interfaces, all within Docker containers that run consistently across machines. Users can pull a particular stack image and launch a Jupyter server without worrying about installing Python, R, or complex dependencies themselves — everything needed is baked into the container. This makes the stacks especially useful for education, demos, collaborative coding, and CI/CD workflows where consistent environments are crucial, and it integrates smoothly with cloud platforms, JupyterHub deployments, and Binder for interactive sharing. -
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OPENRNDR
Kotlin library for creative coding, real-time and interactive graphics
...With these integrations, Machine Learning has become more accessible for interactive designers, coders, and developers. -
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Hypothesis
The property-based testing library for Python
Hypothesis is a powerful library for property-based testing in Python. Instead of writing specific test cases, users define properties and Hypothesis generates random inputs to uncover edge cases and bugs. It integrates with unittest and pytest, shrinking failing examples to minimal reproducible cases. Widely adopted in production systems, Hypothesis boosts code reliability by exploring input spaces far beyond manually crafted tests. -
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Google Kubernetes Engine (GKE) Samples
Sample applications for Google Kubernetes Engine (GKE)
...It serves as a practical companion to official GKE tutorials, providing real, runnable code that illustrates how containerized applications are packaged, deployed, and scaled within Kubernetes clusters. The repository is organized into multiple categories such as AI and machine learning, autoscaling, networking, observability, security, and cost optimization, allowing developers to explore specific use cases and architectural patterns. It includes both simple quickstart examples, like basic “hello world” applications, and more advanced scenarios such as migrating monolithic applications to microservices, implementing service meshes, and configuring custom autoscaling metrics. -
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peepDB
CLI tool and python library to inspect databases fast
peepDB is an open-source command-line tool and Python library designed for developers and database administrators who need a fast and efficient way to inspect their database tables without writing SQL queries. With support for MySQL, PostgreSQL, and MariaDB, peepDB is lightweight, secure, and incredibly easy to use. -
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Yao Open Prompts
A Chinese AI prompt vocabulary covering work, learning, content, etc.
Yao Open Prompts is an open-source AI prompt library focused on real work, study, content, marketing, education, and everyday use cases. The repository organizes 116 Chinese prompt files into practical categories and also provides synchronized English versions. Each prompt is cleaned and structured for reuse, keeping the copyable prompt body while removing promotional material, screenshots, and irrelevant formatting from the original collection. The library includes prompts for meta-prompt... -
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Google CTF
Google CTF
Google CTF is the public repository that houses most of the challenges from Google’s Capture-the-Flag competitions since 2017 and the infrastructure used to run them. It’s a learning and practice archive: competitors and educators can replay tasks across categories like pwn, reversing, crypto, web, sandboxing, and forensics. The code and binaries intentionally contain vulnerabilities—by design—so users can explore exploit chains and patching in realistic settings. The repo also includes... -
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Computer Science courses video lectures
List of Computer Science courses with video lectures
This repository is a curated list of full-length computer science video lecture series across many universities and MOOC platforms, helping learners assemble their own curriculum. The list spans foundational topics like algorithms, data structures, operating systems, computer networks, machine learning, and more, all delivered via lectures rather than just textual tutorials. The contributor guidelines encourage adding high-quality courses (not just casual tutorials) so the list remains academically oriented. Because it’s updated and community maintained, the collection grows with new offerings and helps learners evaluate what courses are available before starting. ... -
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CoreNet
CoreNet: A library for training deep neural networks
CoreNet is Apple’s internal deep learning framework for distributed neural network training, designed for high scalability, low-latency communication, and strong hardware efficiency. It focuses on enabling large-scale model training across clusters of GPUs and accelerators by optimizing data flow and parallelism strategies. CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. Its distributed... -
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PyQuil
A Python library for quantum programming using Quil
PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. PyQuil serves three main functions. PyQuil has a ton of other features, which you can learn more about in the docs. 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... -
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DeepMatch
A deep matching model library for recommendations & advertising
DeepMatch is an open-source deep matching library built for recommendation and advertising systems. It helps developers train models that learn vector representations for users and items. These representations can be exported and used in approximate nearest neighbor search for large-scale retrieval. The library supports familiar Keras workflows through model.fit() and model.predict(). Its model collection includes FM, DSSM, YouTubeDNN, NCF, SDM, MIND, and ComiRec. It is designed to make... -
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PaperSpine
Motivation-driven skill for learning from strong academic papers
PaperSpine is a motivation-driven writing skill suite for academic papers, reports, reviews, and technical manuscripts. It is built for AI tools such as Codex, Claude Code, and OpenClaw, where the agent can follow structured writing workflows. The project asks the agent to study target formats and strong examples before drafting or revising. It emphasizes the central motivation of a paper, helping writers connect claims, structure, evidence, citations, and revisions into a coherent argument....
