Data Science

This book, along with the materials it provides access to, offers a guided path to learning the art of data science. Engage in weekly activities and learn how to ask a good question, explore datasets, and to use models to develop solid statistical evidence. In addition to the materials in the book, you will get access to lecture videos, receive emails with bonus material, and have access to videos of the authors discussing their views on each session’s activities.

Byte size QlikView recipes to solve real world business discovery problems and build effective visualization.

Understand the Office features to improve productivity and optimize your time.

Discover the story of your data by learning the essential elements of statistical associations and correlations in medical research, from the basics of data collection all the way to visualising your relationships. Discover the world of associations and correlations. Get this book, TODAY!

The software that's managing your data shouldn't be a mystery. MySQL is the most popular open source database and powers WordPress, Drupal, Joomla, Magento and more. You don't have to be a professional database designer to understand and make use of its tools. MySQL Explained provides a clear and accessible step-by-step tutorial that will enable you to understand how your data is being stored and even design your own custom applications!

'Big Data' is certainly a cultural and business phenomenon. But what challenges do Data Scientists face in their day-to-day jobs. This collection of interviews with thought-leaders with experience at firms such as Etsy, Spotify, Amazon, Shopify and Stitchfix is an invaluable read to anyone working as a data scientist or managing a team. --------------------- To help support the scientific programming and data analysis community all proceeds from this book will be donated to NumFOCUS.

This book will teach you two things: how to make high quality statistical charts, and how to do it fast. The tool we’ll use is a R package called ezplot, which I wrote to help me with my consulting work. After working through this book, you will be able to create any of the top 10 most used charts in less than 1 minute.

This book introduces a formal framework for measuring ignorance (or nescience) and for guiding scientific discovery. Grounded in computability theory, Kolmogorov complexity, and artificial intelligence, the book analyzes how representations and models encode knowledge, and how their limitations can be quantified. The result is a new perspective on unknown unknowns, perfect knowledge, and the limits of science. For readers interested in artificial intelligence, scientific discovery, and the foundations of knowledge.

Data is messy and cleaning it can be time-consuming and costly – but it doesn’t have to be this way. If you're organised and follow a few simple rules your data cleaning processes can be simple, fast and effective.Practical Data Cleaning explains the 19 most important tips about data cleaning to get your data analysis-ready in double quick time.

This book teaches you how to use data analysis and machine learning to predict bad loan customers based on their applications and demographic data. It is a step-by-step guide, starting from data cleaning, descriptive and exploratory analysis, data visualization, and finishing at model building and backtesting. Each step is accompanied by a set of R code that are ready to use in your own projects with no or little modifications.

Data Science simplified, jargon nullifiedSimple way to understand what actually is Data Science and what Data Scientists actually do

Modern AI applications are not built from scratch but, instead, by integrating off-the-shelf components: libraries, frameworks, and services. "Applied Artificial Intelligence - An Engingeering Approach" focuses on engineering user friendly, high-performance, and maintainable AI applications.

FLOSS4Science Interviews with leaders of the scientific open source software community Vol. 2

FLOSS4Science Interviews with leaders of the scientific open source software community Vol. 1