Hadoop & Data Science NLP (All in One Course).

所在平台: Udemy

课程主页: https://www.udemy.com/course/hadoop-datascience-nlp-all-in-one-course/

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课程简介

课程名称:全方位Hadoop与数据科学自然语言处理课程 概述:随着大数据Hadoop开发者、架构师、数据科学家和机器学习工程师的需求日益增加,企业越来越渴望通过数据实现更准确的预测和分析,以便提供360度的客户视图,从而改善客户体验。本课程旨在帮助学员理解Hadoop和数据科学的精髓,不仅能够直接从源头获取数据并执行与Hadoop相关的操作,还能进行数据科学特定的任务,构建收集到的数据模型。同时,学员还将学习使用Hadoop生态系统工具进行数据转化。简而言之,本课程将帮助学员在一个课程中掌握Hadoop与数据科学自然语言处理的知识技能。 本课程涵盖现代ELT(提取、加载和转化)及分析的完整流程:从数据源获取数据 -> 加载为结构化/半结构化/非结构化形式 -> 执行转化 -> 进一步预处理数据 -> 构建数据科学模型 -> 可视化结果。学员将学习并开始使用流行的Hadoop生态系统技术,以及数据科学中最热门的主题之一——自然语言处理。 在本课程中,学员将能够:使用Hortonworks Sandbox进行Hadoop安装,进行Hadoop操作和Hadoop管理服务(Amabri)的实践;执行HDFS操作以处理连续数据流;安装SSH和文件传输相关工具以支持Hadoop的操作活动;进行NIFI安装,并在Web UI上开发完整的数据工作流,执行数据转化;部署Apache Solr以实现全文搜索,并进行实时文本分析;利用Banana Dashboard可视化实时流数据分析;将实时流的JSON数据存储在Hive表中,并以HDFS中的平面文件格式存储;使用Apache Zeppelin将数据可视化为图表和直方图;学习自然语言处理的基本构建模块,发展文本分析技能;利用数据科学自然语言处理释放机器学习能力,构建机器学习模型对文本数据进行分类。 本课程将是希望掌握这两种技能的专业人士的一个良好起点,因为许多公司(如Google、Amazon、Facebook、Ebay、LinkedIn、Twitter和Yahoo!)都在大规模应用Hadoop,并且越来越多的公司开始采纳这些数字技术。

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课程详情

The demand for Big Data Hadoop Developers, Architects, Data Scientists, Machine Learning Engineers is increasing day by day and one of the main reason is that companies are more keen these days to get more accurate predictions & forecasting result using data. They want to make sense of data and wants to provide 360 view of customers thereby providing better customer experience. This course is designed in such a way that you will get an understanding of best of both worlds i.e. both Hadoop as well as Data Science. You will not only be able to perform Hadoop related operations to gather data from the source directly but also they can perform Data Science specific tasks and build model on the data collected. Also, you will be able to do transformations using Hadoop Ecosystem tools. So in a nutshell, this course will help the students to learn both Hadoop and Data Science Natural Language Processing in one course. Companies like Google, Amazon, Facebook, Ebay, LinkedIn, Twitter, and Yahoo! are using Hadoop on a larger scale these days and more and more companies have already started adopting these digital technologies. If we talk about Text Analytics, there are several applications of Text Analytics (given below) and hence companies prefer to have both of these skillset in the professionals. One of the application of text classification is a faster emergency response system can be developed by classifying panic conversation on social media.Another application is automating the classification of users into cohorts so that marketers can monitor and classify users based on how they are talking about products, services or brands online.Content or product tagging using categories as a way to improve browsing experience or to identify related content on the website. Platforms such as news agencies, directories, E-commerce, blogs, content curators, and likes can use automated technologies to classify and tag content and products. Companies these days are leaning towards candidates who are equipped with best of both worlds and this course will proved to be a very good starting point. This course covers complete pipeline of modern day ELT (Extract, Load and Transform) and Analytics as shown below: Get data from Source -> Load data into Structured/Semi Structured/Unstructured form -> Perform Transformations -> Pre-process the Data further -> Build the Data Science Model -> Visualize the Results Learn and get started with the popular Hadoop Ecosystem technologies as well one the most of the most hot topics in Data Science called Natural Language Processing. In this course you will: Do Hadoop Installation using Hortonworks Sandbox. You will also get an opportunity to do some hands-on with Hadoop operations as well as Hadoop Management Service called Amabri on your computer.Perform HDFS operations to work with continuous stream of data.Install SSH and File Transfer related tools which helps in operational activities of Hadoop.Perform NIFI installation and develop complete workflow on Web UI to move the data from source to destination. Also, perform transformations on this data using NIFI processors.Spin up Apache Solr which allows full text search and also to receive text for performing Real Time Text Analysis.Engage Banana Dashboard to visualize Real Time Analytics on streaming data.Store the Real Time streaming JSON data in structured form using Hive Tables as well as in flat file format in HDFS.Visualize the data in the form of Charts, Histograms using Apache Zappelin.Learn the Building blocks of Natural Language Processing to develop Text Analytics Skills.Unleash the Machine Learning capabilities using Data Science Natural Language Processing and build a Machine Learning Model to classify Text Data.

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