Mastering Numerical Computing with NumPy: Master the skills necessary for performing complex numerical computations and effective data manipulation

Extend the power of NumPy and start boosting your scientific computing capabilities.About This Book* Grasp all aspects of numerical computing and understand NumPy* Loaded with examples to learn EDA, Regression and Clustering* Access NumPy libraries, do performance benchmark to select the right toolWho This Book Is ForIf you are a python programmer, data analyst, data engineer or a data science enthusiast who wants to master the intricacies of NumPy, then this book is for you to build solutions for your numeric and scientific computational problems. Readers are expected to have familiarity with mathematics to get the most out of this book.What You Will Learn* Performing vector and matrix math using NumPy.* Perform exploratory data analysis on US Housing data using NumPy* Develop a predictive model using simple and multiple linear regression* Learn unsupervised learning and clustering algorithms with a use case* Write better NumPy codes and learn to implement the algorithms* Perform benchmark tests to choose the right configuration for a systemIn DetailThe book begins with a quick tour to NumPy library, its syntax structure, coding commands, indexing, slicing, arrays and so on. The readers will then be familiarized with linear algebra concepts and will be able to perform vector and matrix math using NumPy.The book will get you to extend your data analysis capabilities and how you can start performing data manipulation, exploratory data analysis, predictive modeling and how you can boost the performance of NumPy. In the second module, readers will use NumPy statistics to explore United States Housing data and how to develop a predictive model using simple and multiple linear regression. The readers then learn about unsupervised learning and clustering algorithms and use them on a real-life use case. The book will then equip the reader to write better NumPy codes and advanced considerations to be kept in mind. In the final module, readers will learn about different high-performance numerical computing libraries and their relationship with NumPy and perform benchmark tests and choose the appropriate configuration for their own system.By the end of this book, you will achieve the expert competency in handling and performing complex data manipulation and start sailing on the journey of machine learning engineers and data scientists.