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所在平台: Udemy |
课程主页: https://www.udemy.com/course/learning-path-data-science-with-apache-spark-2/
课程评论：没有评论
课程名称：数据科学学习路径：Apache Spark 2 课程概述： Apache Spark 的真正力量和价值在于其快速的数据处理和数据科学任务执行能力。这门课程由一系列视频组成，以逻辑和分步的方式呈现，使每个视频的内容都建立在前一个视频所学的技能之上。Spark 是一种广泛使用的大规模数据处理引擎，运行速度极快。它的框架提供了对应用程序开发人员和数据科学家都非常有用的工具。Spark 独特的用例是结合了 ETL、批量分析、实时流处理、机器学习、图处理和可视化，使数据科学家能够应对来自原始非结构化数据集的复杂性。 这个学习路径将以 Apache Spark 2 的介绍为开端，涉及 Spark 的基础知识、SparkR 的介绍、Python 结合 Spark 数据处理的图表和绘图功能，以及详细的 Spark 数据处理库的使用。课程中还将开发一个现实世界的 Spark 应用程序，并通过对推文数据集的分析，帮助学员舒适自信地使用 Spark 进行数据科学。课程旨在引导学员学习 Apache Spark 2 的数据处理及数据科学库，使其具备现代数据科学家的技能。 授课团队： - Rajanarayanan Thottuvaikkatumana（Raj）：拥有 23 年软件开发经验的资深技术专家，曾在多家跨国公司工作，涉及架构设计和软件开发，专注于大数据技术和应用程序开发平台。 - Eric Charles：数据科学领域具有 10 年经验，是 Datalayer 的创始人，专注于构建高效的数据处理、机器学习算法和结果共享，热衷于开源并积极参与 Apache 社区。 通过这门课程，学员能够掌握 Apache Spark 的核心知识，应用其工具与技术来解决实际数据科学问题。
The real power and value proposition of Apache Spark is its speed and platform to execute data processing and data science tasks. Sounds interesting? Let's see how easy it is! Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. Spark is one of the most widely-used large-scale data processing engines and runs extremely fast. It is a framework that has tools that are equally useful for application developers as well as data scientists. Spark's unique use case is that it combines ETL, batch analytics, real-time stream analysis, machine learning, graph processing, and visualizations to allow data scientists to tackle the complexities that come with raw unstructured datasets. This Learning Path starts with an introduction tour of Apache Spark 2. We will look at the basics of Spark, introduce SparkR, then look at the charting and plotting features of Python in conjunction with Spark data processing, and finally take a thorough look at Spark's data processing libraries. We then develop a real-world Spark application. Next, we will help you become comfortable and confident working with Spark for data science by exploring Spark's data science libraries on a dataset of tweets. The goal of this course to introduce you to Apache Spark 2 and teach you its data processing and data science libraries so that you are equipped with the skills required from modern data scientists. This Learning Path is authored by some of the best in their fields. Rajanarayanan Thottuvaikkatumana Rajanarayanan Thottuvaikkatumana, or Raj, is a seasoned technologist with more than 23 years of software development experience at various multinational companies. His experience includes architecting, designing, and developing software applications. He has worked on various technologies including major databases, application development platforms, web technologies, and big data technologies. Currently he is building a next generation Hadoop YARN-based data processing platform and an application suite built with Spark using Scala. Eric Charles Eric Charles has 10 years' experience in the field of Data Science and is the founder of Datalayer, a social network for Data Scientists. His typical day includes building efficient processing with advanced machine learning algorithms, easy SQL, streaming and graph analytics. He also focuses a lot on visualization and result sharing. He is passionate about open source and is an active Apache Member. He regularly gives talks to corporate clients and at open source events.
