5 个仓库
Awesome GitHub RepositoriesPython Data Science Primers
Introductory educational resources covering Python programming, NumPy arrays, Pandas DataFrames, and visualization libraries for data exploration.
Distinct from Python Data Science Courses: No existing candidate specifically covers the combination of Python basics, arrays, DataFrames, and visualization in a single primer. Closest candidate [f4_mt1] is a course list, not a singular primer resource.
Explore 5 awesome GitHub repositories matching artificial intelligence & ml · Python Data Science Primers. Refine with filters or upvote what's useful.
Awesome Python Data Science Primers GitHub Repositories
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- morvanzhou/tutorials
MorvanZhou/tutorials
12,952在 GitHub 上查看This repository is a comprehensive collection of instructional guides and practical examples for Python development, focusing on machine learning, data science, and web scraping. It provides implementations for neural networks, reinforcement learning algorithms, and deep learning architectures using PyTorch, alongside detailed manuals for scientific computing and data visualization. The project distinguishes itself by offering specialized tutorials on concurrent programming to optimize CPU performance and guides for setting up Linux development environments. It covers the implementation of ad
Provides introductory educational resources covering NumPy arrays, Pandas DataFrames, and visualization libraries for data exploration.
Pythonmachine-learningmultiprocessingneural-network - jvns/pandas-cookbook
jvns/pandas-cookbook
7,086在 GitHub 上查看这是一个 pandas 数据分析实战手册和 Python 数据科学指南。它提供了一系列用于清理、操作和分析结构化数据的编程配方和示例。 该项目专注于提供容器化的分析环境，以确保在执行数据处理脚本时拥有一致的工作空间和可复现的依赖项。 它涵盖了广泛的数据科学功能，包括从外部源进行数据摄取、原始数据清理和探索性数据分析。这些配方演示了如何通过过滤、聚合分组数据和处理文本数据等技术进行结构化数据分析。
Serves as a reference guide for importing datasets and applying mathematical functions to extract insights from real-world information.
Jupyter Notebook - mrdbourke/zero-to-mastery-ml
mrdbourke/zero-to-mastery-ml
5,839在 GitHub 上查看本项目是一个机器学习教育课程和学习平台，通过交互式 Jupyter Notebooks 提供。它作为掌握 Python 数据科学工具包的综合指南，为数值计算、表格数据操作和统计可视化提供结构化教程。 该课程包括 Scikit-Learn 的具体实现指南，以及关于构建、训练和部署神经网络及计算机视觉模型的 TensorFlow 实践课程。它涵盖了构建预测模型的端到端过程，从初始问题定义和任务分类，到通过交互式 Web 界面部署模型。 该项目涵盖了广泛的功能领域，包括多维数组的数值计算、探索性数据分析和数据预处理例程。它为监督和无监督学习、自动化机器学习流水线、超参数优化以及使用分类指标和交叉验证的模型评估提供了详细的工作流。 教育内容组织为一系列 Notebook，将 Python 代码与叙述性解释交织在一起，以记录数据科学工作流。
Offers introductory guides covering Python programming, NumPy arrays, Pandas DataFrames, and Matplotlib for data science exploration.
Jupyter Notebookdata-sciencedeep-learningmachine-learning - allendowney/thinkstats2
AllenDowney/ThinkStats2
4,212在 GitHub 上查看ThinkStats2 是一门计算统计学课程及教育库，旨在通过编程方式教授概率与统计。它提供了一个框架，通过编写 Python 代码并在真实数据集上运行模拟来学习统计概念。 该项目使用交互式笔记本和一系列 Python 模块来提供引导式课程。它强调通过迭代计算实验和基于模拟的测试来验证理论统计定律。 该资源涵盖了数据分析和数据科学培训的广泛功能，允许用户在可编程环境中探索数据集并执行统计分析。
Builds a foundation in data science by applying statistical techniques to datasets using Python libraries.
Jupyter Notebook - visualize-ml/book6_first-course-in-data-science
Visualize-ML/Book6_First-Course-in-Data-Science
2,603在 GitHub 上查看This project is a structured data science curriculum and Python-based textbook designed to teach the fundamentals of data science through executable scripts and hands-on lessons. It functions as a guided programming tutorial for data manipulation and analysis within the Python ecosystem. The content covers introductory machine learning, including the implementation of basic models and algorithms, alongside Python data analysis for cleaning and processing datasets. The material is delivered via Jupyter Notebooks, combining modular exercises and markdown-driven documentation to map theoretical
Serves as a comprehensive primer on data science fundamentals using NumPy, Pandas, and visualization libraries.
Jupyter Notebookdatadata-sciencedata-visualization
