{"product_id":"advanced-analytics-with-pyspark-patterns-for-learning-from-data-at-scale-using-python-and-spark-paperback","title":"Advanced Analytics with Pyspark: Patterns for Learning from Data at Scale Using Python and Spark - Paperback","description":"\u003cp\u003eby \u003cb\u003eAkash Tandon\u003c\/b\u003e (Author), \u003cb\u003eSandy Ryza\u003c\/b\u003e (Author), \u003cb\u003eUri Laserson\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThe amount of data being generated today is staggering and growing. Apache Spark has emerged as the de facto tool to analyze big data and is now a critical part of the data science toolbox. Updated for Spark 3.0, this practical guide brings together Spark, statistical methods, and real-world datasets to teach you how to approach analytics problems using PySpark, Spark's Python API, and other best practices in Spark programming. \u003c\/p\u003e\u003cp\u003e Data scientists Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen, and Josh Wills offer an introduction to the Spark ecosystem, then dive into patterns that apply common techniques-including classification, clustering, collaborative filtering, and anomaly detection, to fields such as genomics, security, and finance. This updated edition also covers NLP and image processing. \u003c\/p\u003e\u003cp\u003e If you have a basic understanding of machine learning and statistics and you program in Python, this book will get you started with large-scale data analysis. \u003c\/p\u003e\u003cul\u003e \u003cli\u003eFamiliarize yourself with Spark's programming model and ecosystem \u003c\/li\u003e\n\u003cli\u003eLearn general approaches in data science \u003c\/li\u003e\n\u003cli\u003eExamine complete implementations that analyze large public datasets \u003c\/li\u003e\n\u003cli\u003eDiscover which machine learning tools make sense for particular problems \u003c\/li\u003e\n\u003cli\u003eExplore code that can be adapted to many uses \u003c\/li\u003e\n\u003c\/ul\u003e\u003ch3\u003eAuthor Biography\u003c\/h3\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eAkash Tandon is an independent consultant and experienced full-stack data engineer. Previously, he was a senior data engineer at Atlan, where he built software for enterprise data science teams. In another life, he had worked on data science projects for governments, and built risk assessment tools at a FinTech startup. As a student, he wrote open source software with the R project for statistical computing and Google. In his free time, he researches things for no good reason.\u003c\/p\u003e\u003cp\u003eSandy Ryza is software engineer at Elementl. Previously, he developed algorithms for public transit at Remix and was a senior data scientist at Cloudera and Clover Health. He is an Apache Spark committer, Apache Hadoop PMC member, and founder of the Time Series for Spark project.\u003c\/p\u003e\u003cp\u003eUri Laserson is founder \u0026amp; CTO of Patch Biosciences. Previously, he worked on big data and genomics at Cloudera.\u003c\/p\u003e\u003cp\u003eSean Owen is a principal solutions architect focusing on machine learning and data science at Databricks. He is an Apache Spark committer and PMC member, and co-author Advanced Analytics with Spark. Previously, he was director of Data Science at Cloudera and an engineer at Google.\u003c\/p\u003e\u003cp\u003eJosh Wills is an independent data science and engineering consultant, the former head of data engineering at Slack and data science at Cloudera, and wrote a tweet about data scientists once.\u003c\/p\u003e\u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 233\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.51 x 9.14 x 6.98 IN\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003eIllustrated:\u003c\/strong\u003e Yes\u003c\/div\u003e\u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e July 19, 2022\u003c\/div\u003e","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":42124693012615,"sku":"9781098103651","price":65.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0601\/2623\/2711\/files\/43cef82377b7d573e726a9a9b281b8ec.webp?v=1732572081","url":"https:\/\/booksby.splitshops.com\/products\/advanced-analytics-with-pyspark-patterns-for-learning-from-data-at-scale-using-python-and-spark-paperback","provider":"Books by splitShops","version":"1.0","type":"link"}