Practical Data Science Cookbook is perfect for those who want to learn data science and numerical programming concepts through hands-on, real-world project examples. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of data science projects, the steps in the data science pipeline, and the programming examples presented in this book.
This is a sponsored post by Richard Heimann. Rich is Chief Data Scientist at L-3 NSS and recently published Social Media Mining with R (Packt Publishing, 2014) with co-author Nathan Danneman, also a Data Scientist at L-3 NSS Data Tactics. Nathan has been featured at recent Data Science DC and DC NLP meetups. Nathan Danneman and Richard Heimann have teamed up with DC2 to organize a giveaway of their new book, Social Media Mining with R.
Over the new two weeks five lucky winners will win a digital copy of the book. Please keep reading to find out how you can be one of the winners and learn more about Social Media Mining with R.
Overview: Social Media Mining with R
Social Media Mining with R is a concise, hands-on guide with several practical examples of social media data mining and a detailed treatise on inference and social science research that will help you in mining data in the real world.
Whether you are an undergraduate who wishes to get hands-on experience working with social data from the Web, a practitioner wishing to expand your competencies and learn unsupervised sentiment analysis, or you are simply interested in social data analysis, this book will prove to be an essential asset. No previous experience with R or statistics is required, though having knowledge of both will enrich your experience. Readers will learn the following:
- Learn the basics of R and all the data types
- Explore the vast expanse of social science research
- Discover more about data potential, the pitfalls, and inferential gotchas
- Gain an insight into the concepts of supervised and unsupervised learning
- Familiarize yourself with visualization and some cognitive pitfalls
- Delve into exploratory data analysis
- Understand the minute details of sentiment analysis
How to Enter?
All you need to do is share your favorite effort in social media mining or more broadly in text analysis and natural language processing in the comments section of this blog. This can be some analytical output, a seminal white paper or an interesting commercial or open source package! In this way, there are no losers as we will all learn.
The first five commenters will win a free copy of the eBook. (DC2 board members and staff are not eligible to win.) Share your public social media accounts (about.me, Twitter, LinkedIn, etc.) in your comment, or email email@example.com after posting.