Introduction to my data science book

@machinelearnbot

Click here to view more details about the book. This book is a type of "handbook" on data science and data scientists, and contains information not found in traditional statistical, programming, or computer science textbooks. The author has compiled what he considers some of the most important information you will need for a career in data science, based on his 20 years as a leader in the field. Much of the text was initially published on the Data Science Central website over the last three years, which is read by millions of website visitors. The book shows how data science is different from related fields and the value it brings to organizations using big data. This book has three components: a multi-layer discussion of what data science is and how it relates to other disciplines; technical applications of and for data science including tutorials and case studies; and career resources for practicing and aspiring data scientists. Numerous career and training resources are included (such as data sets, web crawler source code, data videos, and how to build API's) so you can start practicing data science today and quickly boost your career. For decision makers, you will find information to help you make decisions on how to build a better analytic team, whether and when you need specialized solutions, and which ones will work best for your need.


Introduction to my data science book

@machinelearnbot

Click here to view more details about the book. This book is a type of "handbook" on data science and data scientists, and contains information not found in traditional statistical, programming, or computer science textbooks. The author has compiled what he considers some of the most important information you will need for a career in data science, based on his 20 years as a leader in the field. Much of the text was initially published on the Data Science Central website over the last three years, which is read by millions of website visitors. The book shows how data science is different from related fields and the value it brings to organizations using big data.


Free Book: Statistics -- New Foundations, Toolbox, and Machine Learning Recipes

#artificialintelligence

This book is intended for busy professionals working with data of any kind: engineers, BI analysts, statisticians, operations research, AI and machine learning professionals, economists, data scientists, biologists, and quants, ranging from beginners to executives. In about 300 pages and 28 chapters it covers many new topics, offering a fresh perspective on the subject, including rules of thumb and recipes that are easy to automate or integrate in black-box systems, as well as new model-free, data-driven foundations to statistical science and predictive analytics. The approach focuses on robust techniques; it is bottom-up (from applications to theory), in contrast to the traditional top-down approach. The material is accessible to practitioners with a one-year college-level exposure to statistics and probability. The compact and tutorial style, featuring many applications with numerous illustrations, is aimed at practitioners, researchers, and executives in various quantitative fields.


Best Data Science Books

#artificialintelligence

There is much debate among scholars and practitioners about what data science is, and what it isn't. Does it deal only with big data? Is data science really that new? How is it different from statistics and analytics? One way to consider data science is as an evolutionary step in interdisciplinary fields like business analysis that incorporate computer science, modeling, statistics, analytics, and mathematics.


Fast-Track, On-Demand, No-Fee Program to Become a Data Scientist

@machinelearnbot

We have re-designed our online, accelerated data science apprenticeship: it is now available to anyone, at no cost, with no restrictions, and does not require any application nor deadlines. Data sets, a cheat sheet to get you started, real-life projects to work on, sample code, and tons of resources, are provided on DSC, and are regularly updated, including very recently. The presentation style is compact. This is an ideal program for professionals with a quantitative background and some industry experience - in a nutshell, for anyone who understands our cheat sheet and can get started using it. This program is for self-learners.