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From 0 to 1 : Spark for Data Science with Python

教程/Tutorials Goldy 0评论
Duration: 8h 19m | Video: h264, 1280x720 | Audio: AAC, 44100 Hz, 2 Ch | 10 GB
Genre: eLearning | Language: English | Project Files

Video Description

Get your data to fly using Spark for analytics, machine learning and data science Let’s parse that. What's Spark? If you are an analyst or a data scientist, you're used to having multiple systems for working with data. SQL, Python, R, Java, etc. With Spark, you have a single engine where you can explore and play with large amounts of data, run machine learning algorithms and then use the same system to productionize your code.Analytics: Using Spark and Python you can analyze and explore your data in an interactive environment with fast feedback. The course will show how to leverage the power of RDDs and Dataframes to manipulate data with ease. Machine Learning and Data Science : Spark's core functionality and built-in libraries make it easy to implement complex algorithms like Recommendations with very few lines of code. We'll cover a variety of datasets and algorithms including PageRank, MapReduce and Graph datasets.

Style and Approach

A 8 hour high-quality courses available at super low prices to cover Spark, Machine Learning and Data Science

Table of Contents

YOU, THIS COURSE AND US
INTRODUCTION TO SPARK
RESILIENT DISTRIBUTED DATASETS
ADVANCED RDDS: PAIR RESILIENT DISTRIBUTED DATASETS
ADVANCED SPARK: ACCUMULATORS, SPARK SUBMIT, MAPREDUCE, BEHIND THE SCENES
JAVA AND SPARK
PAGERANK: RANKING SEARCH RESULTS
SPARK SQL
MLLIB IN SPARK: BUILD A RECOMMENDATIONS ENGINE
SPARK STREAMING
GRAPH LIBRARIES

What You Will Learn

Use Spark for a variety of analytics and Machine Learning tasks
Implement complex algorithms like PageRank or Music Recommendations
Work with a variety of datasets from Airline delays to Twitter, Web graphs, Social networks and Product Ratings
Use all the different features and libraries of Spark : RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming and GraphX

Authors

Loonycorn

Loonycorn is Janani Ravi and Vitthal Srinivasan. Between them, they have studied at Stanford, been admitted to IIM Ahmedabad and have spent years working in tech, in the Bay Area, New York, Singapore and Bangalore.

Janani: 7 years at Google (New York, Singapore); Studied at Stanford; also worked at Flipkart and Microsoft

Vitthal: Also Google (Singapore) and studied at Stanford; Flipkart, Credit Suisse and INSEAD too.

They think they might have hit upon a neat way of teaching complicated tech courses in a funny, practical, engaging way, which is why they are so excited to be here. They hope you will try our offerings, and you'll like them 🙂

 

From 0 to 1 : Spark for Data Science with Python

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网友最新评论 (1)

  1. 从零到一:使用Python学习Spark数据科学 使用Spark进行分析、机器学习和数据科学,可以让你的数据飞起来。什么是Spark?如果你是一名分析师或是一名数据科学家,你会经常使用多套系统用于处理数据,如SQL、Python、R、Java等。使用Spark,你可以通过单一引擎处理海量数据、运行机器学习算法,然后使用同一套系统将代码产品和。通过本教程的学习,你可以以在一种具有快速反馈的互动环境中分析和探索数据。本教程将会为你讲授如何利用RDDs和Dataframes的功能轻松地处理数据。Spark的核心功能和内建类库令部署如Recommendations这样的复杂算法只需要几行代码。我们将会学习到抱哈PageRank、MapReduce和Graph的各种数据集合算法。 主要内容: • 使用Spark用于各种分析和机器学习任务 • 部署如页面排名或音乐推荐这样的复杂算法 • 处理从航空延迟到Twitter、Web graph、社交网络和产品排名各种的数据集 使用Spark所有不同的功能和类库:RDDs、Dataframes、Spark、SQL、MLlib、Spark Streaming和Graphx
    wilde(特殊组-翻译)2个月前 (10-02)