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Machine Learning with Spark and Python Essential Techniques for Predictive Analytics, Second Edition simplifies ML for practical uses by;
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want to implement various machine-learning concepts in the context of Spark ML, this book is for you. You should be well versed with the Scala and;
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* Learn why and how you can efficiently use Python to process data and build machine learning models in Apache Spark 2.0 * Develop and deploy;
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This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale;
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, machine learning, and analytics using PySpark Overcome challenges in developing and deploying Spark solutions using Python Explore recipes for;
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data sets. But Spark goes much further than other frameworks. By including machine learning and graph processing capabilities, it makes;
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Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models;
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Create, execute, modify, and share machine learning applications with Python and TensorFlow 2.0 in the Jupyter Notebook environment. This;
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Taming Big Data with Apache Spark and Python is your companion to learning Apache Spark in a hands-on manner. Frank will start you off by;
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recommendation systems. With Building Machine Learning Systems with Python, you'll gain the tools and understanding required to build your own systems;
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Python makes machine learning easy for beginners and experienced developers With computing power increasing exponentially and costs;
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success. This guide is meant to help you with understanding the fundamentals of Machine Learning with Python, as well as making predictions and;
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working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark * Comprehensive practical;
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present book tries to address IoT, Python and Machine Learning along with a small introduction to Image Processing. If you are a novice programmer;
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present book tries to address IoT, Python and Machine Learning along with a small introduction to Image Processing. If you are a novice programmer;
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* Build machine learning systems with Spark that can detect fraud and analyze financial risks * Build predictive models focusing on customer;
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Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries;
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Get up and running with the basics of geographic information systems (GIS), geospatial analysis, and machine learning on spatial data;
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learning engineers who want to get started with IBM Cloud and its machine learning services using practical examples. Basic knowledge of Python and;
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learning applications using Spark MLlib and how to manage the machine learning development lifecycle. This book is packed with practical examples;
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, and machine learning, so that the reader can not only employ statistical and machine learning models using modern Python modules, but also;
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Inside this book you will find all the basic notions to start with Python and all the programming concepts to build machine learning;
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case studies with Python code and domain-specific innovative ideas for monetizing machine learning. What You Will Learn Discover applied;
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data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive;
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input data-has revolutionized the way we do business. Applied Supervised Learning with Python provides a rich understanding of how you can apply;
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