Practical Python Data Visualization: A Fast Track Approach to Learning Data Visualization with Python (Pajankar Ashwin)(Paperback)

Practical Python Data Visualization: A Fast Track Approach to Learning Data Visualization with Python (Pajankar Ashwin)(Paperback)

Chapter 1: Data Visualization with LeatherChapter Goal: Introduce readers to the data visualization with a simple library leatherNo of pages: 15Sub - Topics: 1. Introduction to leather2. Installation to leather3. Various types of graphs with leatherChapter 2: Introduction to the Scientific Python

Data Visualization: Exploring and Explaining with Data (Camm Jeffrey D.)(Paperback)

DATA VISUALIZATION: Exploring and Explaining with Data is designed to introduce best practices in data visualization to undergraduate and graduate students. This is one of the first books on data visualization designed for college courses. The book contains material on effective design, choice of

Python for Data Science: The Ultimate Beginners' Guide to Learning Python Data Science Step by Step (Williams Ethan)(Paperback)

Humanities Data Analysis: Case Studies with Python (Karsdorp Folgert)(Pevná vazba)

A practical guide to data-intensive humanities research using the Python programming languageThe use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers to discover patterns in a vast range of source materials

Thoughtful Machine Learning with Python: A Test-Driven Approach (Kirk Matthew)(Paperback)

Gain the confidence you need to apply machine learning in your daily work. With this practical guide, author Matthew Kirk shows you how to integrate and test machine learning algorithms in your code, without the academic subtext. Featuring graphs and highlighted code examples throughout, the book

Interactive Data Visualization for the Web: An Introduction to Designing with D3 (Murray Scott)(Paperback)

Create and publish your own interactive data visualization projects on the web--even if you have little or no experience with data visualization or web development. It's inspiring and fun with this friendly, accessible, and practical hands-on introduction. This fully updated and expanded second

Practical Data Science with Python 3: Synthesizing Actionable Insights from Data (Varga Ervin)(Paperback)

Chapter 1. Introduction to Data ScienceNo of pages: 10This chapter introduces the reader to data science, and describes the major stages of working with data (collect, explore, preprocess, visualize, predict, and infer knowledge). It sets the common expectations what constitutes a data science

Learn Quantum Computing with Python and Q#: A Hands-On Approach (Kaiser Sarah C.)(Paperback)

Learn Quantum Computing with Python and Q# introduces quantum computing from a practical perspective. Summary Learn Quantum Computing with Python and Q# demystifies quantum computing. Using Python and the new quantum programming language Q#, you'll build your own quantum simulator and apply quantum

Real-World Python: A Hacker's Guide to Solving Problems with Code (Vaughan Lee)(Paperback)

A project-based approach to learning Python programming for beginners. Intriguing projects teach you how to tackle challenging problems with code. You've mastered the basics. Now you're ready to explore some of Python's more powerful tools. Real-World Python will show you how. Through a series of

Visual Data Storytelling with Tableau (Ryan Lindy)(Paperback)

Tell Insightful, Actionable Business Stories with Tableau, the World's Leading Data Visualization Tool Visual Data Storytelling with Tableau brings together knowledge, context, and hands-on skills for telling powerful, actionable data stories with Tableau. This full-color guide shows how to

Python for Data Science for Dummies (Mueller John Paul)(Paperback)

Python is a general-purpose programming language that is popular with data scientists. It is free, as are a number of open-source libraries help acquire, organize, and process information. This book is designed for beginners to data analysis and covers the basics of Python data analysis programming

Machine Learning: Concepts, Tools and Data Visualization (Kang Minsoo)(Paperback)

This set of lecture notes, written for those who are unfamiliar with mathematics and programming, introduces the reader to important concepts in the field of machine learning. It consists of three parts. The first is an overview of the history of artificial intelligence, machine learning, and data

Data Visualization: A Practical Introduction (Healy Kieran)(Paperback)

An accessible primer on how to create effective graphics from dataThis book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using

Python Scripting for Arcgis Pro (Zandbergen Paul A.)(Paperback)

The definitive, easy-to-follow guide to writing Python code with spatial data in ArcGIS Pro, whether you're new to programming or not. Python Scripting for ArcGIS Pro starts with the fundamentals of Python programming and then dives into how to write useful Python scripts that work with spatial

Python Data Structures and Algorithms: Improve application performance with graphs, stacks, and queues (Baka Benjamin)(Paperback)

Implement classic and functional data structures and algorithms using Python Key Features A step by step guide, which will provide you with a thorough discussion on the analysis and design of fundamental Python data structures. Get a better understanding of advanced Python concepts such as big-o

Visual Analytics with Tableau (Loth Alexander)(Paperback)

A four-color journey through a complete Tableau visualization Tableau is a popular data visualization tool that's easy for individual desktop use as well as enterprise. Used by financial analysts, marketers, statisticians, business and sales leadership, and many other job roles to present data

Introduction to Machine Learning with Python: A Guide for Data Scientists (Mller Andreas C.)(Paperback)

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning

Core Data Analysis: Summarization, Correlation, and Visualization (Mirkin Boris)(Paperback)

This text examines the goals of data analysis with respect to enhancing knowledge, and identifies data summarization and correlation analysis as the core issues. Data summarization, both quantitative and categorical, is treated within the encoder-decoder paradigm bringing forward a number of

Data-Driven Security - Analysis, Visualization and Dashboards (Jacobs Jay)(Paperback / softback)

Uncover hidden patterns of data and respond with countermeasures Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful ? data analysis and

Efficient R Programming: A Practical Guide to Smarter Programming (Gillespie Colin)(Paperback)

There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively--until now. This hands-on book

Bioinformatics Programming Using Python: Practical Programming for Biological Data (Model Mitchell L.)(Paperback)

Powerful, flexible, and easy to use, Python is an ideal language for building software tools and applications for life science research and development. This unique book shows you how to program with Python, using code examples taken directly from bioinformatics. In a short time, you'll be using

Python Data Persistence: With SQL and NOSQL Databases (Lathkar Malhar)(Paperback)

Designed to provide an insight into the SQL and MySQL database concepts using python. Key Features A practical approach Ample code examples A Quick Start Guide to Python for beginners Description Python is becoming increasingly popular among data scientists. However, analysis and visualization

Programming with Python for Social Scientists (Brooker Phillip)(Paperback)

As data become 'big', fast and complex, the software and computing tools needed to manage and analyse them are rapidly developing. Social scientists need new tools to meet these challenges, tackle big datasets, while also developing a more nuanced understanding of - and control over - how these

Machine Learning Pocket Reference: Working with Structured Data in Python (Harrison Matt)(Paperback)

With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine