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<p><b>Learn the techniques and math you need to start making sense of your data</b></p>Key Features<ul><li>Enhance your knowledge of coding with the theory for practical insight in data science and analysis</li><li>More than just a math class; you’ll perform real-world data science tasks using Python</li><li>Get the best insights and transform your data to get tangible value out of it</li><li></li></ul>Book DescriptionNeed to turn programming skills into effective data science skills? This book helps you connect mathematics, programming, and business analysis. You’ll feel confident asking—and answering—complex, sophisticated questions of your data, making abstract and raw statistics into actionable ideas.<br/>Going through the data science pipeline, you'll clean and prepare data and learn effective data mining strategies and techniques to gain a comprehensive view of how the data science puzzle fits together. You’ll learn fundamentals of computational mathematics and statistics and pseudo-code used by data scientists and analysts. You’ll learn machine learning, discovering statistical models that help control and navigate even the densest datasets, and learn powerful visualizations that communicate what your data means.<br/>What you will learn<ul><li>Understand five most important steps of data science</li><li>Use your data intelligently and learn how to handle it with care</li><li>Bridge the gap between mathematics and programming</li><li>Drive actionable results and clean your data using statistical models, calculus, and probability</li><li>Build and evaluate baseline machine learning models</li><li>Explore effective metrics to determine the success of your machine learning models</li><li>Create data visualizations that communicate actionable insights</li><li>Apply machine learning concepts to your problems and make actual predictions</li><li></li></ul>Who this book is forIf you are an aspiring data scientist who wants to take your first steps in data science, thi