Amazon Top 20 Books in Data Mining
These are the most popular data mining books on Amazon. As you look to increase your knowledge, is there something listed here that is missing from your collection?
on Oct 27, 2015 in Amazon, Book, Data Mining
New Books on Accelerating Discovery, Event Mining, Networking for Big Data
New books cover important Data Science topics, including Mining Unstructured Information for Hypothesis Generation, Event Mining, and Networking for Big Data. Use GZP42 to save 20%.
on Oct 23, 2015 in Big Data, Book, CRC Press, Event Mining, Network Science, Process Mining, Unstructured data
Infographic – Data Scientist or Business Analyst? Knowing the Difference is Key
Infographic depicting unique differences between data scientists and business analysts. Find out what type of professional is needed to meet your organization’s needs.
on Oct 20, 2015 in Business Analyst, Data Scientist, Education, Infographic, Jobs
Lavastorm – 5 Tips to Get More From Tableau
Tableau makes it easy for users to see the data, but data preparation for it is hard. This free ebook highlights how to overcome Tableau challenges with data access, data blending, advanced analytics, transparency and reusability.
on Oct 20, 2015 in Data Preparation, Free ebook, Lavastorm, Tableau
Dell: The Great Analytics Migration – free e-book
If you want to switch to an analytics platform with more functionality and less cost, how to manage all the people, processes and technologies involved? We just wrote the e-book on it - after we moved hundreds of our employees to a new analytics solution.
on Oct 15, 2015 in Analytics, Dell, Free ebook, Migration
90+ Active Blogs on Analytics, Big Data, Data Mining, Data Science, Machine Learning
Stay on top of your data science skills game! Here's a list of 90+ active blogs on Big Data, Data Science, Data Mining, Machine Learning, and Artificial intelligence.
on Oct 8, 2015 in Big Data, Blogs, Data Science, Deep Learning, Hadoop, Machine Learning
Top 5 arXiv Deep Learning Papers, Explained
Top deep learning papers on arXiv are presented, summarized, and explained with the help of a leading researcher in the field.
on Oct 1, 2015 in arXiv, Deep Learning, Explained, Hugo Larochelle