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所在平台: Udemy |
课程主页: https://www.udemy.com/course/jupyter-notebook-for-data-science/
课程评论：没有评论
课程名称: Jupyter Notebook for Data Science 课程概述: 本视频课程将帮助您熟悉Jupyter Notebook及其所有功能，以在Python中执行各种数据科学任务。Jupyter Notebook是一个强大的交互式数据探索和可视化工具，已成为数据科学家使用的标准工具。课程将从基本的数据分析任务入手，逐步学习一些常见的科学Python工具，如pandas、matplotlib和plotly。我们将使用真实数据集，例如纽约市的犯罪和交通事故数据，探索数据抓取和清洗等常见问题。课程中，我们将创建有洞察力的可视化，展示时间戳和空间数据。到课程结束时，您将能够自信地处理新数据集，进行数据清洗、探索和分析，提取有用信息，并生成交互式报告和信息丰富的数据可视化。本课程使用Jupyter 5.4.1版本，尽管不是最新版本，但对数据科学爱好者提供相关和有益的内容。 关于作者: Dražen Lucanin 是开发者、数据分析师，同时也是Punk Rock Dev的创始人，这是一家独立的网络开发工作室。自2009年以来，他专业从事基于Python、JavaScript等技术的网络应用程序开发和数据分析。过去，Dražen曾担任研究助理，并在维也纳科技大学攻读计算机科学博士学位，研究地理分布的数据中心的能源效率，优化基于实时电价和天气条件的虚拟机调度。他还作为外部合作研究员在鲁德尔·博斯科维奇研究所，从事机器学习方法在金融危机预测中的应用。在他从事科学工作的过程中，Python、Jupyter Notebook（当时称为IPython Notebook）、Matplotlib和Pandas在处理各种时间序列和空间数据的交互操作中是他的得力助手。Dražen还获得了萨格勒布大学的计算机科学硕士学位。 无教学大纲。
This video course will help you get familiar with Jupyter Notebook and all of its features to perform various data science tasks in Python. Jupyter Notebook is a powerful tool for interactive data exploration and visualization and has become the standard tool among data scientists. In the course, we will start from basic data analysis tasks in Jupyter Notebook and work our way up to learn some common scientific Python tools such as pandas, matplotlib, and plotly. We will work with real datasets, such as crime and traffic accidents in New York City, to explore common issues such as data scraping and cleaning. We will create insightful visualizations, showing time-stamped and spatial data.By the end of the course, you will feel confident about approaching a new dataset, cleaning it up, exploring it, and analyzing it in Jupyter Notebook to extract useful information in the form of interactive reports and information-dense data visualizations.This course uses Jupyter 5.4.1, while not the latest version available, it provides relevant and informative content for data science enthusiasts.About the AuthorDražen Lucanin is a developer, data analyst, and the founder of Punk Rock Dev, an indie web development studio. He's been building web applications and doing data analysis in Python, JavaScript, and other technologies professionally since 2009. In the past, Dražen worked as a research assistant and did a PhD in computer science at the Vienna University of Technology. There he studied the energy efficiency of geographically distributed datacenters and worked on optimizing VM scheduling based on real-time electricity prices and weather conditions. He also worked as an external associate at the Ruder Boškovic Institute, researching machine learning methods for forecasting financial crises. During Dražen's scientific work Python, Jupyter Notebook (back then still IPython Notebook), Matplotlib, and Pandas were his best friends over many nights of interactive manipulation of all sorts of time series and spatial data. Dražen also did a Master's degree in computer science at the University of Zagreb.
