Learn the fundamentals of data science with Python by analyzing real datasets and solving problems using pandasKey FeaturesLearn how to apply data retrieval, transformation, visualization, and modeling techniques using pandasBecome highly efficient in unlocking deeper insights from your data, including databases, web data, and moreBuild your experience and confidence with hands-on exercises and activitiesBook DescriptionThe P...

This book exists to help you work more wisely. We, at Minerva Work Solutions, recognize the investment we all make in our jobs and we know we can do more to help ourselves and our communities by promoting humane and effective work practices.In the interest of putting something into your hands to use exactly when you need it, we've boiled down our experience and research into 50 practical tips. Each tip is presented in short segments. We've also categorized these tips as primarily re...

With knowledge and information shared by experts, take your first steps towards creating scalable AI algorithms and solutions in Python, through practical exercises and engaging activitiesKey FeaturesLearn about AI and ML algorithms from the perspective of a seasoned data scientistGet practical experience in ML algorithms, such as regression, tree algorithms, clustering, and moreDesign neural networks that emulate the human brainB...

Data Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today’s data science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the data science pipeline. Author Michael Brzustowicz explains the basic math theory behind each step of the data science process, as well as how to apply these concepts with Java.You’ll learn the critica...

Enhance the power of NumPy and start boosting your scientific computing capabilitiesKey FeaturesGrasp all aspects of numerical computing and understand NumPyExplore examples to learn exploratory data analysis (EDA), regression, and clusteringAccess NumPy libraries and use performance benchmarking to select the right toolBook DescriptionNumPy is one of the most important scientific computing libraries available for Python. Mas...

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 you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process.Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduct...

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsKey FeaturesLeverage Python’s most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effective strategies and best practices to improve and optimize machine learning systems and algorithmsAsk – and answer – tough questions of your data with robust statistical models, built for a range of datasets...

A poorly performing database application not only costs users time, but also has an impact on other applications running on the same computer or the same network. SQL Tuning provides an essential next step for SQL developers and database administrators who want to extend their SQL tuning expertise and get the most from their database applications.There are two basic issues to focus on when tuning SQL: how to find and interpret the execution plan of an SQL statement and how to chan...

If you’re considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports.Updated for R 2.14 and 2.15, this second edition includes...

R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly.The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anon...

Named a Notable Book in the 21st Annual Best of Computing list by the ACM!Robert Sedgewick and Kevin Wayne’s Computer Science: An Interdisciplinary Approach is the ideal modern introduction to computer science with Java programming for both students and professionals. Taking a broad, applications-based approach, Sedgewick and Wayne teach through important examples from science, mathematics, engineering, finance, and commercial computing.The book de...

Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries.Key FeaturesSecond edition of the bestselling book on Machine LearningA practical approach to key frameworks in data science, machine learning, and deep learningUse the most powerful Python libraries to implement machine learning and deep learningGet to know the best practices to improve and optimize you...