Books

A set of exercises for working with water data in ArcGIS, containing mostly new exercises I haven't published elsewhere - still a work in progress. Prior experience in GIS is assumed (see http://coursera.org/learn/gis for my courses that you can audit for free or take for a certificate)

This book breaks down the mystique around modern artificial intelligence and guides you through the world of self-driving cars, facial recognition, and digital voice assistants.

The next time you look at an matrimonial advertisement in a news paper or a web age, your brain is going to break down the text and give you social insights and understand the direction the society is headed to. Here is your opportunity to learn and experiment not just on text mining but also web parsing. Get your hands dirty now.

Data science is a growing field. Want to learn the popular python programming language to do data mining, this is the book to grab.

Learn to scale your data science projects from comfort of your development laptop to production scale on the Google and Amazon Clouds. Learn Python for Data Science. Setup Google Cloud Datastore, Firebase, and DynamoDB. Use Neo4j and Open Refine in your workflow.

What do Atari games, schedule planning and self-piloted drones have in common? Find the answer in this book!

Want to quickly build dashboards to get insight from your data, but don't want to spend on expensive software? Do you need a data-driven app that helps your business? Do you have a general interest in web development, but don't know were to start? Shiny can do this and more for you. This book helps you get started to get your work done.

Understand the whole process of what is Natural Language Processing, not just bits and pieces. Build practical application, with real-world data. Crawl, clean, build models, fine-tune and deploy.

This book covers R software development for building data science tools. This book provides rigorous training in the R language and covers modern software development practices for building tools that are highly reusable, modular, and suitable for use in a team-based environment or a community of developers. (Printed copies coming soon!)

Photobiology is the branch of science that studies the interactions of living organisms with visible and ultraviolet radiation. This book first presents the theory behind calculations related to research in photobiology and describes how to use R as a tool for carrying out these calculations.

Wir haben nicht zu wenige, sondern zu viele Informationen. Das ist das Neue unseres Zeitalters. Modernes Informationsmanagement hat deshalb als erste Herausforderung: Wie organisieren wir das Vergessen? Server und E-Mail-Fächer quellen über, ToDo-Listen werden immer länger. Eine strukturierte Vorgehensweise, mit diesem Problem umzugehen, gibt es bislang nicht. Die 2. Herausforderung für den Umgang mit Informationen: Wie schaffen wir den Übergang von einer Einzelkämpferkultur zu einer Kooperationskultur? Wer Informationen braucht, hat oft keinen Zugriff darauf. Auch im 21. Jahrhundert organisieren wir die Verwaltung von Dokumenten und Aufgaben oft noch in abgeschotteten Silos. Ein hoher unproduktiver Synchronisationsaufwand in Form interner E-Mails, Telefonaten und Sitzungen ist die Folge. Das Buch schlägt den Übergang zu einem Denken in Vorgängen vor. Daraus ergeben sich Lösungen für beide Fragestellungen. Denn Kern der Wertschöpfung und Weiterentwicklung eines Unternehmens ist das Abschließen von Vorgängen. Organisiert man die Verwaltung von Dokumenten und E-Mails nach dieser Logik, kann man den Zugriff der Teams auf ihre Vorgänge einfach organisieren. Und auch das Aussondern nicht mehr benötigter Dokumente macht keine Umstände mehr.

This book teaches you to design, analyze, and draw meaningful conclusions from experiments and observational studies.  Experiments such as A/B testing and observational data obtained by scraping the web, are commonly encountered in data science.  Many examples are also included from the sciences and social sciences.

A neural network simulation from 1974, based on Marr's Model of Cerebellar Cortex.

Python is one of the top 3 tools that Data Scientists use. One of the tools in their arsenal is the Pandas library. This tool is popular because it gives you so much functionality out of the box. In addition, you can use all the power of Python to make the hard stuff easy! 

A series on writing effective, idiomatic pandas.