The work is also eminently suitable for professionals on continuous education short courses, and to researchers following self-study courses. Found insideStyle and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. "Designed to teach people to program even if they have no prior experience. Found insideThis book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you’ll have the solid foundation you need to start a career in data science. With this handbook, you'll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: ... This book offers up-to-date insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas, and scikit-learn. Then this is the guidebook for you! In this guidebook, we are going to spend some time exploring the basics of data science, and how we can go through each of the steps to get this process to work for you. Found inside – Page 1Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. This book is the ideal introduction to data science with Microsoft SQL Server and In-Database ML Services. This book will help readers get comfortable with using the Python environment for data science and will start them on a journey to mastering topics within machine learning. This book content also covers the basic questions which are asked during an interview. This book is mainly intended to help people represent their answer in a sensible way to the interviewer. If you need help writing programs in Python 3, or want to update older Python 2 code, this book is just the ticket. Found insideIn this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. This book explains: Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, ... WHO THIS BOOK IS FOR The book is for readers with basic programming and mathematical skills. The book is for any engineering graduates that wish to apply data science in their projects or wish to build a career in this direction. Found insideThe book also discusses Google Colab, which makes it possible to write Python code in the cloud. Found insideA Tour of Data Science: Learn R and Python in Parallel covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single short book. Found insideKeep this handy quick guide at your side whether you're a student, an entry-level data science professional converting from R to Python, or a seasoned Python developer who doesn't want to memorize every function and option. Presents case studies and instructions on how to solve data analysis problems using Python. The book aligns with the latest ACM/IEEE CS-and-related computing curriculum initiatives and with the Data Science Undergraduate Curriculum Proposal sponsored by the National Science Foundation. And Data Science with Python and Dask is your guide to using Dask for your data projects without changing the way you work! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. This book aims to equip you with just enough knowledge of Python in conjunction with skills to use powerful tool such as Jupyter Notebook in order to succeed in the role of a data scientist. Ê The book starts with a brief introduction to ... We hope this book will be the starting point for your journey into the fascinating world of Data Science. To get started on your Python adventure, just scroll back up and click the 'Buy' button. This book synthesizes both fundamental and advanced topics of a research area that has now reached maturity. The chapters of this book are organized into three sections: The first section is an introduction to data science. "This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience"-- As it also provides some statistics background, the book can be used by anyone who wants to perform a statistical data analysis. Found insideThe book begins with an overview of the place of data science in the humanities, and proceeds to cover data carpentry: the essential techniques for gathering, cleaning, representing, and transforming textual and tabular data. This book covers: Introduction to Python and data analysis Python basics Python history Installing Python Data analysis with Python NumPy for numerical data processing Data visualization with Python Machine learning with Python And much ... Found insideWith this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas ... And this is what you will learn in Python Data Science. You will learn about the main steps that are needed to correctly implement Data Science techniques and the algorithms to help you sort through the data and see some amazing results. This book is for you. This book is written for beginners and novices who want to develop fundamental data science skills and learn how to build models that learn useful information from data. This book will teach Python to complete beginners through a set of 3 practical projects. This book presents some of the most important modeling and prediction techniques, along with relevant applications. DESCRIPTION Machine Learning does not have to be intimidating at all. This book focuses on the concepts of Machine Learning and Data Analytics with mathematical explanations and programming examples. Data Science Projects with Python will help you get comfortable with using the Python environment for data science. This book will start you on your journey to mastering topics within machine learning. And this is what you will learn in Python Data Science. You will learn about the main steps that are needed to correctly implement Data Science techniques and the algorithms to help you sort through the data and see some amazing results. Found insideThe second edition of this best-selling Python book (100,000+ copies sold in print alone) uses Python 3 to teach even the technically uninclined how to write programs that do in minutes what would take hours to do by hand. Found insideSo if you want to make a career change and become a data scientist, now is the time. This book will guide you through the process. Found inside – Page iThis book covers the most popular Python 3 frameworks for both local and distributed (in premise and cloud based) processing. Style and approach This book is an easy-to-follow, comprehensive guide on data science using Python. The topics covered in the book can all be used in real world scenarios. Long story short--Python is simply a high-priority data science tool. How Is This Book Different? The book focuses equally on the theoretical as well as practical aspects of data science. Found insideThis book covers the fundamentals of machine learning with Python in a concise and dynamic manner. How Is This Book Different? Every book by AI Publishing has been carefully crafted. This book lays equal emphasis on the theoretical sections as well as the practical aspects of data science. Python Machine Learning for Beginners is the guide for you. Python Machine Learning for Beginners is the ultimate guide for beginners looking to learn and understand how Python programming works. Drawing on machine learning and data science concepts, this book broadens the range of tools that you can use to transform the market analysis process. Data Science Using Python and R provides exercises at the end of every chapter, totaling over 500 exercises in the book. 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