Search Results for "python programming"
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32 projects for "python programming" with 2 filters applied:
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Python Programming Hub
Learn Python and Machine Learning from scratch
Python Programming Hub repository by Tanu-N-Prabhu is an educational resource designed to help programmers learn Python programming and data science concepts through practical examples and notebooks. The project contains a wide range of tutorials and exercises that cover Python fundamentals, programming concepts, and applied techniques for data analysis and machine learning. -
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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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Amazing-Python-Scripts
Curated collection of Amazing Python scripts
Amazing-Python-Scripts is a collaborative repository that collects a wide variety of Python scripts designed to demonstrate practical programming techniques and automation tasks. The project includes scripts ranging from beginner-level utilities to more advanced applications involving machine learning, data processing, and system automation. Its goal is to provide developers with useful coding examples that can solve everyday problems, automate repetitive tasks, or serve as learning exercises. ... -
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GPU Puzzles
Solve puzzles. Learn CUDA
GPU Puzzles is an educational project designed to teach GPU programming concepts through interactive coding exercises and puzzles. Instead of presenting traditional lecture-style explanations, the project immerses learners directly in hands-on programming tasks that demonstrate how GPU computation works. The exercises are implemented using Python with the Numba CUDA interface, which allows Python code to compile into GPU kernels that run on CUDA-enabled hardware. ... -
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python-small-examples
Focus on creating classic Python small examples and cases
python-small-examples is an open-source educational repository that contains hundreds of concise Python programming examples designed to illustrate practical coding techniques. The project focuses on teaching programming concepts through small, focused scripts that demonstrate common tasks in data processing, visualization, and general programming. -
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Book6_First-Course-in-Data-Science
From Addition, Subtraction, Multiplication, and Division to ML
Book6_First-Course-in-Data-Science is an open-source educational project that serves as part of the “Iris Book” series focused on teaching data science and machine learning concepts through a combination of mathematics, programming, and visualization. The repository contains draft chapters, supporting Python code, and visual materials designed to guide readers from basic mathematical operations toward practical machine learning understanding. The goal of the project is to make complex topics such as statistics, algorithms, and data analysis more accessible to learners by breaking concepts into clear explanations supported by code examples and diagrams. ... -
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qxresearch-event-1
Python hands on tutorial with 50+ Python Application
qxresearch-event-1 is an open-source educational repository that provides a collection of lightweight Python applications designed to demonstrate programming concepts and artificial intelligence techniques in simple and accessible examples. The repository contains dozens of small programs, many implemented with minimal lines of code, covering topics such as machine learning, graphical user interfaces, computer vision, and API integration. -
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machine_learning_examples
A collection of machine learning examples and tutorials
machine_learning_examples is an open-source repository that provides a large collection of machine learning tutorials and practical code examples. The project aims to teach machine learning concepts through hands-on programming rather than purely theoretical explanations. It includes implementations of many machine learning algorithms and neural network architectures using Python and popular libraries such as TensorFlow and NumPy. The repository covers a wide range of topics including supervised learning, unsupervised learning, reinforcement learning, and natural language processing. ... -
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TorchCode
Practice implementing softmax, attention, GPT-2 and more
TorchCode is an interactive learning and practice platform designed to help developers master PyTorch by implementing core machine learning operations and architectures from scratch. It is structured similarly to competitive programming platforms like LeetCode but focuses specifically on tensor operations and deep learning concepts. The platform provides a collection of curated problems that cover fundamental topics such as activation functions, normalization layers, attention mechanisms,... -
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Diffrax
Numerical differential equation solvers in JAX
Diffrax is a numerical differential equation solving library built for the JAX ecosystem, with a strong focus on composability, differentiability, and high-performance scientific computing. The project provides tools for solving ordinary differential equations, stochastic differential equations, controlled differential equations, and related systems in a way that fits naturally into modern machine learning and differentiable programming workflows. Because it is written to work closely with... -
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DATA SCIENCE ROADMAP
Data Science Roadmap from A to Z
...The project presents a structured roadmap that outlines the knowledge and skills required for different stages of a data science career. Topics typically include programming with Python, statistics, mathematics, machine learning algorithms, data visualization, and big data technologies. The roadmap also includes links to courses, tutorials, and external resources that help learners study each topic in more depth. By organizing these subjects into a logical sequence, the repository helps beginners understand how different technical skills connect within the broader data science workflow. ... -
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Deepnote
Deepnote is a drop-in replacement for Jupyter
...Built on top of the Jupyter kernel ecosystem, it maintains compatibility with existing notebook workflows while introducing additional features focused on collaboration and automation. The system supports programming languages such as Python, R, and SQL and allows users to execute and analyze data directly within interactive notebooks. Deepnote emphasizes team-based data science by enabling real-time collaboration similar to shared document editors, allowing multiple users to work simultaneously on the same notebook environment. -
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Text2Code for Jupyter notebook
A proof-of-concept jupyter extension which converts english queries
Text2Code for Jupyter notebook project is a proof-of-concept extension for Jupyter Notebook that allows users to generate Python code directly from natural language queries written in English. The tool is designed to simplify data analysis workflows by enabling users to describe their intended operation in plain language instead of manually writing code. When a user enters a textual command, the extension interprets the request and generates a corresponding Python code snippet that can be... -
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TensorFlow Quantum
Open-source Python framework for hybrid quantum-classical ml learning
TensorFlow Quantum is an open-source software framework designed for building and training hybrid quantum-classical machine learning models within the TensorFlow ecosystem. The framework enables researchers and developers to represent quantum circuits as data and integrate them directly into machine learning workflows. By combining classical deep learning techniques with quantum algorithms, the platform allows experimentation with quantum machine learning methods that may offer advantages... -
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Data Science Interviews
Data science interview questions and answers
Data Science Interviews is an open-source repository that collects common data science interview questions along with community-provided answers and explanations. The project serves as a preparation resource for students, job seekers, and professionals who want to review the technical knowledge required for data science roles. The repository organizes questions into different categories including theoretical machine learning concepts, technical programming questions, and probability or... -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads:... -
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Ai-Learn
The artificial intelligence learning roadmap compiles 200 cases
...The repository was created to help learners start self-study programs in artificial intelligence without getting overwhelmed by the large number of available resources. It organizes topics such as Python programming, mathematics for machine learning, data analysis, deep learning, computer vision, and natural language processing into a structured learning path. The project also provides a large collection of practical exercises and case studies that allow learners to apply theoretical knowledge through real projects. According to the repository description, it includes nearly two hundred hands-on AI examples developed through years of teaching experience. -
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Tensor Puzzles
Solve puzzles. Improve your pytorch
Tensor Puzzles is an interactive collection of 21 exercises for learning tensor programming in PyTorch and NumPy. Each puzzle asks the learner to recreate a familiar array operation from first principles. Solutions must fit on one short line and use only a restricted set of indexing, arithmetic, comparison, and broadcasting tools. Standard convenience functions such as sum, view, squeeze, and take are intentionally prohibited. This constraint encourages a deeper understanding of shapes,... -
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scikit-learn-videos
Jupyter notebooks from the scikit-learn video series
...Each video corresponds to a notebook that walks through the code step by step, allowing students to see both the theoretical explanation and its practical implementation. The project emphasizes accessibility and beginner-friendly explanations, making it suitable for learners who are new to data science or machine learning programming. The tutorials collectively span several hours of instructional content and demonstrate how to build predictive models using Python tools commonly used in the data science ecosystem. -
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Mars Framework
Mars is a tensor-based unified framework for large-scale data
Mars is a distributed computing framework designed to scale scientific computing and data science workloads across large clusters while preserving the familiar programming interfaces of common Python libraries. The project provides a tensor-based execution model that extends the capabilities of tools such as NumPy, pandas, and scikit-learn so that large datasets can be processed in parallel without rewriting code for distributed environments. Its architecture automatically divides large computational tasks into smaller chunks that can be executed across multiple nodes in a cluster, allowing complex analytics, machine learning workflows, and data transformations to run efficiently at scale. ... -
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learn-machine-learning-in-two-months
Essential Knowledge for learning Machine Learning in two months
The learn-machine-learning-in-two-months repository is an educational open-source project designed to guide beginners through the process of learning machine learning and deep learning concepts within a structured two-month study plan. The project compiles curated resources, tutorials, and practical notebooks that introduce fundamental topics such as mathematics for machine learning, Python programming, and essential libraries like NumPy and TensorFlow. It progressively moves from foundational theory to more advanced subjects including regression, classification, neural networks, and model deployment. The repository emphasizes understanding the underlying principles of machine learning while also providing practical exercises and examples that allow learners to build and experiment with real models. ... -
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CodeSearchNet
Datasets, tools, and benchmarks for representation learning of code
...The dataset contains millions of pairs of source code functions and corresponding documentation comments extracted from open-source repositories. These pairs allow machine learning models to learn relationships between natural language descriptions and programming code. The dataset currently covers several widely used programming languages, including Python, JavaScript, Ruby, Go, Java, and PHP. In addition to the dataset itself, the repository includes baseline models, evaluation tools, and instructions for building code retrieval systems that can map user queries to relevant code snippets. -
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Swift for TensorFlow
Swift for TensorFlow
Swift for TensorFlow repository contains the open-source implementation of Swift for TensorFlow, a project that integrates machine learning capabilities directly into the Swift programming language. The initiative aims to provide a new programming model for developing machine learning systems by combining the power of TensorFlow with language-level features such as automatic differentiation and strong type systems. By embedding machine learning functionality into the Swift compiler and... -
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python-is-cool
Cool Python features for machine learning
python-is-cool is an educational repository created by AI researcher Chip Huyen that explores lesser-known features and powerful capabilities of the Python programming language. The project serves as a curated guide to Python techniques that many developers may overlook or hesitate to use due to unfamiliarity. It demonstrates practical language features, idiomatic programming patterns, and useful tricks that can make Python code more expressive, efficient, and elegant. ... -
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Girls-In-AI
Free learning code series: Xiaobai's introduction to Python
Girls-In-AI is an educational repository created to encourage women and beginners to learn programming and artificial intelligence through accessible tutorials and practice materials. The project provides a collection of beginner-friendly learning resources covering Python programming, data analysis, machine learning, and deep learning topics. It aims to lower the barrier to entry for people who want to enter the field of artificial intelligence by offering structured learning paths and practical examples. ...