Principles of Data Science: Mathematical techniques and theory to succeed in dat

<p><strong>Learn the techniques and math you need to start making sense of your data</strong></p><p><br></p><p><strong>Key Features: </strong></p><ul><li>Enhance your knowledge of coding with data science theory for practical insight into data science and analysis</li><li>More than just a math class, learn how to perform real-world data science tasks with R and Python</li><li>Create actionable insights and transform raw data into tangible value</li></ul><p><strong>Book Description: </strong></p><p>Need to turn your skills at programming into effective data science skills? Principles of Data Science is created to help you join the dots between mathematics, programming, and business analysis. With this book, you'll feel confident about asking-and answering-complex and sophisticated questions of your data to move from abstract and raw statistics to actionable ideas.</p><p></p><p>With a unique approach that bridges the gap between mathematics and computer science, this books takes you through the entire data science pipeline. Beginning with cleaning and preparing data, and effective data mining strategies and techniques, you'll move on to build a comprehensive picture of how every piece of the data science puzzle fits together. Learn the fundamentals of computational mathematics and statistics, as well as some pseudocode being used today by data scientists and analysts. You'll get to grips with machine learning, discover the statistical models that help you take control and navi