Data Science

All Indian Reprints of O'Reilly are Printed in Grayscale. Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show...
AuthorWes McKinney Condition TypeNew
Data is a fantastic raw resource for powering change in an organization, but all too often the people working in those organizations don't have the necessary skills to communicate with data effectively. With this practical book, subject matter experts will learn ways to develop strong, persuasive points when presenting data to different groups in their organizations.
AuthorCarl Allchin BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models.
AuthorAbdullah Karasan BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale Every enterprise application creates data, including log messages, metrics, user activity, and outgoing messages. Learning how to move these items is almost as important as the data itself. If you're an application architect, developer, or production engineer new to Apache Pulsar, this practical guide shows you how to use this open source event streaming platform to handle real-time data feeds.
AuthorJowanza Joseph BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations.
AuthorSusan E. McGregor BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages. Moving all this data is just as important as the data itself. With this updated edition, application...
Author 1Gwen Shapira Author 2Todd Palino
All Indian Reprints of O'Reilly are printed in Grayscale Data is a fantastic raw resource for powering change in an organization, but all too often the people working in those organizations don't have the necessary skills to communicate with data effectively. With this practical book, subject matter experts will learn ways to develop strong, persuasive points when presenting data to different groups in their organizations.
AuthorCarl Allchin BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data pre-processing, model design, model training, evaluation, deployment, and interpretability.
Author 1Valliappa Lakshmanan Author 2Martin Görner
All Indian Reprints of O'Reilly are printed in Grayscale   What's so special about this book? If you've read a Head First book, you know what to expect: a visually rich format designed for the way your brain works. With Head First Design Patterns, 2E you'll learn design principles and patterns in a way that won't put you to sleep, so you can get out there to solve software design problems and speak the language of patterns with others on your team.
Author 1Eric Freeman Author 2Elisabeth Robson
All Indian Reprints of O'Reilly are printed in Grayscale Site reliability engineering (SRE) is more relevant than ever. Knowing how to keepsystems reliable has become a critical skill. With this practical book, newcomers and old hatsalike will explore a broad range of conversations happening in SRE. You'll get actionable adviceon several topics, including how to adopt SRE, why SLOs matter, when you need to upgradeyour incident response, and how monitoring and observability differ.
AuthorEmil Stolarsky Author 2Jaime Woo
All Indian Reprints of O'Reilly are printed in Grayscale Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You’ll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP).  
AuthorHariom Tatsat Author 1Brad Lookabaugh
All Indian Reprints of O'Reilly are printed in Grayscale What value does semantic data modeling offer? As an information architect or data science professional, let's say you have an abundance of the right data and the technology to extract business gold but you still fail. The reason? Bad data semantics.
Author 1Panos Alexopoulos BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale The design patterns in this book capture best practices and solutions to recurring problems in machine learning. Authors Valliappa Lakshmanan, Sara Robinson, and Michael Munn catalog the first tried-and-proven methods to help engineers tackle problems that frequently crop up during the ML process. These design patterns codify the experience of hundreds of experts into advice you can easily follow. 
AuthorValliappa Lakshmanan Author 1Michael Munn
All Indian Reprints of O'Reilly are printed in Grayscale Companies are spending billions on machine learning projects, but it's money wasted if the models can't be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You'll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems.  
AuthorHannes Hapke Author 1Catherine Nelson
All Indian Reprints of O'Reilly are printed in Grayscale If you want to build an enterprise-quality application that uses natural language text but aren't sure where to begin or what tools to use, this practical guide will help get you started. Alex Thomas, principal data scientist at Wisecube, shows software engineers and data scientists how to build scalable natural language processing (NLP) applications using deep learning and the Apache Spark NLP library. 
AuthorAlex Thomas BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. 
Author 1Sowmya Vajjala Author 2Bodhisattwa Majumder
All Indian Reprints of O'Reilly are printed in Grayscale While several market-leading companies have successfully transformed their business models by following data- and AI-driven paths, the vast majority have yet to reap the benefits. How can your business and analytics units gain a competitive advantage by capturing the full potential of this predictive revolution? This practical guide presents a battle-tested end-to-end method to help you translate business decisions into tractable prescriptive solutions using data and AI as fundamental inputs.  
Author 1Daniel Vaughan BindingPaperback
Want to get started on data science? Our promise: no math added. This book has been written in layman's terms as a gentle introduction to data science and its algorithms. Each algorithm has its own dedicated chapter that explains how it works, and shows an example of a real-world application. To help you grasp key concepts, we stick to intuitive explanations and visuals.
AuthorAnnalyn Ng Author 2Kenneth Soo
All Indian Reprints of O'Reilly are printed in Grayscale For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all‘IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.
AuthorJake VanderPlas BindingPaperback