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Data Science for Business: A Definitive Guide to Data Mining, Data Warehousing, Data Analytics, Modelling, Visualization, Regression Analysis
Stefan Campos
Paperback. Stefan Campos 2021-04-01.
ISBN 9781802280142
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Buy from Amazon.co.uk
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Publisher description
55% OFF for Bookstores! NOW at $11.69 instead of $25.99! LAST DAYS ! If any of your bookstore readers are interested in Information Technologies and acquire certifications to advance in their career, there has to be a good reason for it. IT career paths are diverse and specialists certified in any IT sphere get promising salaries starting from Machine Learning Engineers to Data Scientists. Data science brings various scientific methods such as statistics, mathematics, and IT together with expertise to get data to analyze, forecast, and make predictions to submit further information as well as to optimize existing processes. Data Science takes care of collecting, shaping, storing, managing, and analyzing data and it benefits not only small but also established businesses to grow and handle large amounts of data. Your customers will never stop using this awesome book! In the guidebook "Data Science for Business", a profound insight is offered into data mining, warehousing, and analytics that will help you shape a data-driven mindset. Let this book amaze your customers assisting them to manage big data for business and use specialized techniques in the decision-making procedure. There are numerous benefits that "Data Science for Business" offers to its ever-learning readers: Mitigate Risks in Business using Data ScienceHow to Handle and Manage Big Data in Business Machine-learning Algorithms Develop Your Own Data Analytics Strategy and Action Plan, and much more You're probably assured that Data Science is hard to learn, and overall, you might be thinking to yourself "I have no idea what Linear Regression is", or "Algorithms? Hell no!" We've done all the hard work for you and put everything in simple terms
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Data Science for Business: A Definitive Guide to Data Mining, Data Warehousing, Data Analytics, Modelling, Visualization, Regression Analysis
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