{"product_id":"scaling-machine-learning-with-spark-distributed-ml-with-mllib-tensorflow-and-pytorch-paperback-1","title":"Scaling Machine Learning with Spark: Distributed ML with Mllib, Tensorflow, and Pytorch - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eAdi Polak\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eLearn how to build end-to-end scalable machine learning solutions with Apache Spark. With this practical guide, author Adi Polak introduces data and ML practitioners to creative solutions that supersede today's traditional methods. You'll learn a more holistic approach that takes you beyond specific requirements and organizational goals--allowing data and ML practitioners to collaborate and understand each other better.\u003c\/p\u003e \u003cp\u003e\u003cem\u003eScaling Machine Learning with Spark\u003c\/em\u003e examines several technologies for building end-to-end distributed ML workflows based on the Apache Spark ecosystem with Spark MLlib, MLflow, TensorFlow, and PyTorch. If you're a data scientist who works with machine learning, this book shows you when and why to use each technology.\u003c\/p\u003e \u003cp\u003eYou will: \u003c\/p\u003e \u003cul\u003e \u003cli\u003eExplore machine learning, including distributed computing concepts and terminology\u003c\/li\u003e \u003cli\u003eManage the ML lifecycle with MLflow\u003c\/li\u003e \u003cli\u003eIngest data and perform basic preprocessing with Spark\u003c\/li\u003e \u003cli\u003eExplore feature engineering, and use Spark to extract features\u003c\/li\u003e \u003cli\u003eTrain a model with MLlib and build a pipeline to reproduce it\u003c\/li\u003e \u003cli\u003eBuild a data system to combine the power of Spark with deep learning\u003c\/li\u003e \u003cli\u003eGet a step-by-step example of working with distributed TensorFlow\u003c\/li\u003e \u003cli\u003eUse PyTorch to scale machine learning and its internal architecture\u003c\/li\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 291\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.62 x 9.19 x 7 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e April 11, 2023\u003c\/div\u003e\n            \u003c\/ul\u003e","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47212254462201,"sku":"9781098106829","price":79.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/YVl5WnlLcjI3SUo2SzM0VjNCWnE0dz09_f69e9fa7-61fd-4dc4-a026-6d175505a1ef.webp?v=1768088381","url":"https:\/\/bookscloud.io\/products\/scaling-machine-learning-with-spark-distributed-ml-with-mllib-tensorflow-and-pytorch-paperback-1","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}