Python has become one of the most popular programming languages for data science and artificial intelligence. It's a versatile language that offers a wide range of libraries and tools for data analysis, visualization, and machine learning. In this book, "Python Data Science," readers will learn how to use Python to explore and analyze data, create powerful visualizations, and build machine learning models....

The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice.In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatab...

200+ pages of valuable content!Machines can LEARN?!?!Machine learning occurs primarily through the use of " algorithms" and other elaborate procedures.Whether you're a novice, intermediate or expert this book will teach you all the ins, outs and everything you need to know about machine learning.Note: Bonus chapters included inside!Instead of spending hundreds or even thousands of dollars on courses/materials why not read this book instead? Its a wor...

The quality of a data warehouse (DWH) is the elusive aspect of it, not because it is hard to achieve [once we agree what it is], but because it is difficult to describe. We propose the notion that quality is not an attribute or a feature that a product has to possess, but rather a relationship between that product and each and every stakeholder. More specifically, the relationship between the software quality and the organization that produces the products is explored. Quality of data that...

Key FeaturesBook DescriptionUpdated and upgraded to the latest libraries and most modern thinking, Machine Learning with R, Second Edition provides you with a rigorous introduction to this essential skill of professional data science. Without shying away from technical theory, it is written to provide focused and practical knowledge to get you building algorithms and crunching your data, with minimal previous experience. With this book, you'll discover...

This book offers a comprehensive introduction to workflow management, the management of business processes with information technology. By defining, analyzing, and redesigning an organization's resources and operations, workflow management systems ensure that the right information reaches the right person or computer application at the right time. The book provides a basic overview of workflow terminology and organization, as well as detailed coverage of workflow modeling with Petri nets. ...

The book will initially explain the What-Why of Data Science and the process of solving a Data Science problem. The fundamental concepts of Data Science, such as Statistics, Machine Learning, Business Intelligence, Data pipeline, and Cloud Computing, will also be discussed. All the topics will be explained with an example problem and will show how the industry approaches to solve such a problem. The book will pose questions to the learners to solve the problems and build the problem-solvin...

Stay one step ahead of your competitors with proven tips, strategies, and insights from over 30 Kaggle Masters and Grandmasters and become a better data scientist. This new edition features updated content and new chapters on Kaggle Models, time series, and Generative AI competitions. Key FeaturesLearn how Kaggle works to make the most of every competition with winning strategies from 30+ expert KagglersSharpen your modeling skills with feature engineer...

Get your statistics basics right before diving into the world of data science Key FeaturesNo need to take a degree in statistics, read this book and get a strong statistics base for data science and real-world programs;Implement statistics in data science tasks such as data cleaning, mining, and analysisLearn all about probability, statistics, numerical computations, and more with the help of R programsBook DescriptionData sc...

Optimize your marketing strategies through analytics and machine learningKey FeaturesUnderstand how data science drives successful marketing campaignsUse machine learning for better customer engagement, retention, and product recommendationsExtract insights from your data to optimize marketing strategies and increase profitabilityBook DescriptionRegardless of company size, the adoption of data science and machine learning for...

Software Engineering and Object Oriented Modeling: This book is specially written for those who are interested in understanding software engineering and Object Oriented Modeling concepts using UML in the Computer Engineering and Information technology field and want to gain enhanced knowledge about the power of UML Language in software development.Also everyone with interest in learning UML for Software Engineering for application development can refer to this book to get the knowl...

Predictive Analytics with Microsoft Azure Machine Learning, Second Edition is a practical tutorial introduction to the field of data science and machine learning, with a focus on building and deploying predictive models. The book provides a thorough overview of the Microsoft Azure Machine Learning service released for general availability on February 18th, 2015 with practical guidance for building recommenders, propensity models, and churn and predictive maintenance models.