Hands-On Data Science with Anaconda

This book is for developers who are looking for the best tools in the market to perform data science. Existing data analysts and data science professionals who wish to improve the efficiency of their data science applications by using the best libraries in the multiple languages will find this book quite useful. Basic programming knowledge with Python and introductory knowledge of linear algebra is expected. Anaconda is an open source Data Science platform that brings the best tools for data science together. It is a data science stack that Includes more than 100 popular packages based in Python, Scala and R. With the help of its package manager conda, you can work with hundreds of packages in different languages and perform data preprocessing, modelling, clustering, classification, validation and so on with ease. This book will get you started with Anaconda and how you can use it to perform data science operations in real world.You will start off with set up, and get the environment ready for Anaconda platform—Jupyter, installation of relevant packages, and more. You will then cover basics of data science and linear algebra for performing data science tasks. Once you are ready to go, you will start with operations in data science such as cleaning, sorting, and data classification. You will then learn how to perform tasks such as clustering, regression, prediction, building machine learning models, and optimizing them. You will also learn how to visualize data and to share the projects. During this course, you will learn how to use different packages using Anaconda to get the best results. You will know how to efficiently use Conda—the package, dependency, and environment manager for Anaconda.You will also be introduced to several powerful features of Anaconda such as additional projects, project add-ons, shared project drives, powerful compute nodes that are available in the paid version for accomplishing advanced data handling processes. You will learn to build scalable and functionally efficient packages and will be able to perform heterogeneous data exploration, distributed computing and more. You will learn to discover and share packages, notebooks and environments to increase productivity. You will also learn about Anaconda Accelerate, a feature which helps in achieving SLAs easily and optimizing computational power.