54 Results for : ingesting

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    The Essential Organic Gardening Guide Book , Hörbuch, Digital, ungekürzt, 41min
    Do you want to grow your own organic vegetables, herbs, and fruit? But not sure where to start? Have you ever found yourself a little frustrated that anything you try and grow, dies soon after planting and has been a waste of your time, money, and effort? How about simple step-by-step instruction that even the most novice of gardeners can produce amazing, organic food in just a few hours from now? If so, you've found the right book! It's no surprise in this day and age with so much technology, it is often hard to be sure what chemicals you are ingesting with your food. The vegetables you buy from supermarkets may look bright and fresh but did you also know they are constantly sprayed with strong chemicals that can be seriously unhealthy for your body. I know for sure that I'm not going to expose myself or my children to these chemicals, you shouldn't either! By eating non-organic you can have: Low energy levels. A slow metabolism Low libido/sex drive Depression Little to no motivation Organic food can change all of this and give you a completely new outlook on life. You will really notice a huge boost in energy levels! The taste of organic food is not the only advantage. It really does change many aspects of your life. It's time to change your bad habits and start a new life with organic food. I am going to help you along the way so you can set up your very own organic garden as fast as possible. This is a book of action, I have outlined the essentials steps you need to take to know everything that I know of years of research and studying in as little as a couple of hours. That's why I have written this book for you that is in very simple to listen to. I have designed this book to take a complete beginner to to expert (and any one in between) so you can produce amazing, organic food with my instructions. ungekürzt. Language: English. Narrator: JD Kelly. Audio sample: https://samples.audible.de/bk/acx0/101604/bk_acx0_101604_sample.mp3. Digital audiobook in aax.
    • Shop: Audible
    • Price: 9.95 EUR excl. shipping
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    Data Analysis with Python and Pyspark
    Think big about your data! PySpark brings the powerful Spark big data processing engine to the Python ecosystem, letting you seamlessly scale up your data tasks and create lightning-fast pipelines. In Data Analysis with Python and PySpark you will learn how to: Manage your data as it scales across multiple machines Scale up your data programs with full confidence Read and write data to and from a variety of sources and formats Deal with messy data with PySpark's data manipulation functionality Discover new data sets and perform exploratory data analysis Build automated data pipelines that transform, summarize, and get insights from data Troubleshoot common PySpark errors Creating reliable long-running jobs Data Analysis with Python and PySpark is your guide to delivering successful Python-driven data projects. Packed with relevant examples and essential techniques, this practical book teaches you to build pipelines for reporting, machine learning, and other data-centric tasks. Quick exercises in every chapter help you practice what you've learned, and rapidly start implementing PySpark into your data systems. No previous knowledge of Spark is required. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology The Spark data processing engine is an amazing analytics factory: raw data comes in, insight comes out. PySpark wraps Spark's core engine with a Python-based API. It helps simplify Spark's steep learning curve and makes this powerful tool available to anyone working in the Python data ecosystem. About the book Data Analysis with Python and PySpark helps you solve the daily challenges of data science with PySpark. You'll learn how to scale your processing capabilities across multiple machines while ingesting data from any source-whether that's Hadoop clusters, cloud data storage, or local data files. Once you've covered the fundamentals, you'll explore the full versatility of PySpark by building machine learning pipelines, and blending Python, pandas, and PySpark code. What's inside Organizing your PySpark code Managing your data, no matter the size Scale up your data programs with full confidence Troubleshooting common data pipeline problems Creating reliable long-running jobs About the reader Written for data scientists and data engineers comfortable with Python. About the author As a ML director for a data-driven software company, Jonathan Rioux uses PySpark daily. He teaches the software to data scientists, engineers, and data-savvy business analysts. Table of Contents 1 Introduction PART 1 GET ACQUAINTED: FIRST STEPS IN PYSPARK 2 Your first data program in PySpark 3 Submitting and scaling your first PySpark program 4 Analyzing tabular data with pyspark.sql 5 Data frame gymnastics: Joining and grouping PART 2 GET PROFICIENT: TRANSLATE YOUR IDEAS INTO CODE 6 Multidimensional data frames: Using PySpark with JSON data 7 Bilingual PySpark: Blending Python and SQL code 8 Extending PySpark with Python: RDD and UDFs 9 Big data is just a lot of small data: Using pandas UDFs 10 Your data under a different lens: Window functions 11 Faster PySpark: Understanding Spark's query planning PART 3 GET CONFIDENT: USING MACHINE LEARNING WITH PYSPARK 12 Setting the stage: Preparing features for machine learning 13 Robust machine learning with ML Pipelines 14 Building custom ML transformers and estimators
    • Shop: buecher
    • Price: 62.99 EUR excl. shipping
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    Data Analysis with Python and PySpark (eBook, ePUB)
    Think big about your data! PySpark brings the powerful Spark big data processing engine to the Python ecosystem, letting you seamlessly scale up your data tasks and create lightning-fast pipelines. In Data Analysis with Python and PySpark you will learn how to: Manage your data as it scales across multiple machines Scale up your data programs with full confidence Read and write data to and from a variety of sources and formats Deal with messy data with PySpark's data manipulation functionality Discover new data sets and perform exploratory data analysis Build automated data pipelines that transform, summarize, and get insights from data Troubleshoot common PySpark errors Creating reliable long-running jobs Data Analysis with Python and PySpark is your guide to delivering successful Python-driven data projects. Packed with relevant examples and essential techniques, this practical book teaches you to build pipelines for reporting, machine learning, and other data-centric tasks. Quick exercises in every chapter help you practice what you've learned, and rapidly start implementing PySpark into your data systems. No previous knowledge of Spark is required. About the technology The Spark data processing engine is an amazing analytics factory: raw data comes in, insight comes out. PySpark wraps Spark's core engine with a Python-based API. It helps simplify Spark's steep learning curve and makes this powerful tool available to anyone working in the Python data ecosystem. About the book Data Analysis with Python and PySpark helps you solve the daily challenges of data science with PySpark. You'll learn how to scale your processing capabilities across multiple machines while ingesting data from any source-whether that's Hadoop clusters, cloud data storage, or local data files. Once you've covered the fundamentals, you'll explore the full versatility of PySpark by building machine learning pipelines, and blending Python, pandas, and PySpark code. What's inside Organizing your PySpark code Managing your data, no matter the size Scale up your data programs with full confidence Troubleshooting common data pipeline problems Creating reliable long-running jobs About the reader Written for data scientists and data engineers comfortable with Python. About the author As a ML director for a data-driven software company, Jonathan Rioux uses PySpark daily. He teaches the software to data scientists, engineers, and data-savvy business analysts. Table of Contents 1 Introduction PART 1 GET ACQUAINTED: FIRST STEPS IN PYSPARK 2 Your first data program in PySpark 3 Submitting and scaling your first PySpark program 4 Analyzing tabular data with pyspark.sql 5 Data frame gymnastics: Joining and grouping PART 2 GET PROFICIENT: TRANSLATE YOUR IDEAS INTO CODE 6 Multidimensional data frames: Using PySpark with JSON data 7 Bilingual PySpark: Blending Python and SQL code 8 Extending PySpark with Python: RDD and UDFs 9 Big data is just a lot of small data: Using pandas UDFs 10 Your data under a different lens: Window functions 11 Faster PySpark: Understanding Spark's query planning PART 3 GET CONFIDENT: USING MACHINE LEARNING WITH PYSPARK 12 Setting the stage: Preparing features for machine learning 13 Robust machine learning with ML Pipelines 14 Building custom ML transformers and estimators
    • Shop: buecher
    • Price: 42.40 EUR excl. shipping
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    Advanced Analytics in Power BI with R and Python
    Advanced Analytics in Power BI with R and Python - Ingesting Transforming Visualizing: ab 36.99 €
    • Shop: ebook.de
    • Price: 36.99 EUR excl. shipping

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