As a practicing data scientist, I’ve spent years building up my library of academic and practical resources that I routinely draw upon for helping me do my work. Although my library is vast, I have a select group of books that occupy a prominent position on my desk. I’ve been asked enough times about my “favorite titles” list, I thought I’d write this article for my readers.
From the Editor’s Bookshelf: My Favorite Titles for Data Science and Machine Learning
August 29, 2017 by
The Benefits of Having a Data Scientist Career
August 5, 2017 by
Our friends over at Simplilearn provided us the infographic below which explores the advantages of the a data science career and shows you the various roles available in this career path, along with projected salaries from around the globe.
Interview: Mary Cameron, Data Scientist at Tophatter
July 28, 2017 by
I recently caught up with Mary Cameron, Data Scientist at Tophatter, to get her compelling insights into how Tophatter uses the principles of data science. She also delves into her life as a data scientist at a dynamic and growing company.
Defining the Data Science Landscape
July 27, 2017 by
In this contributed article, Manny Bernabe who leads and develops strategic relationships for Uptake’s Data Science team, discusses how it is important to note the distinctions in terminology in the data science landscape. Perhaps most notably, people must be aware of the differences between data science, machine learning and artificial intelligence. The three shouldn’t be used interchangeably due to fundamental differences in their definitions and in what they deliver.
Using Python to Drive New Insights and Innovation from Big Data
July 20, 2017 by
In a recent white paper “Management’s Guide – Unlocking the Power of Data Science & Machine Learning with Python,” ActiveState – the Open Source Language Company – provides a summary of Python’s attributes in a number of important areas, as well as considerations for implementing Python to drive new insights and innovation from big data.
Unlocking the Power of Data Science & Machine Learning with Python
July 14, 2017 by Leave a Comment
The time is now for companies to get started on data science initiatives if they have not already. By addressing these needs early on, data science teams can focus on unlocking the power of their data and driving innovation forward. To learn more download this white paper.
The Rise of the Citizen Data Scientist: Detente in the Era of Data Wars
July 9, 2017 by
In this contributed article, Sri Raghavan, Senior Global Product Marketing Manager for Teradata Aster, highlights how the advent of the era of the Citizen Data Scientist is not to be considered a threat to the Data Scientist in the organization. If anything it helps validate the assertions made by Data Scientists about the power of advanced analytics. Having more people like the Citizen Data Scientists attests to the unbridled power of analytics.
How R Powers Data Science at Microsoft
June 28, 2017 by
In this video “How R Powers Data Science at Microsoft” from the EARL 2017 conference in San Francisco (June 5-7, 2017), insideAI News’s Managing Editor and resident data scientist Daniel D. Gutierrez chats with Vijay K. Narayanan – Director, Algorithms and Data Science Solutions, Microsoft.
Book Review: The Mathematical Corporation by Josh Sullivan and Angela Zutavern
June 23, 2017 by
As a data scientist, I know first hand how today’s enterprise has some catching up to do with engaging the mathematical foundations for capitalizing on an ever-increasing volume of data assets. This is why a new title is so important: “The Mathematical Corporation – Where Machine Intelligence and Human Ingenuity Achieve the Impossible,” by Josh Sullivan and Angela Zutavern. Sullivan and Zutavern are, respectively, senior vice president and vice president of Booz Allen Hamilton.
The Difference Between Data Science and Data Analytics
June 3, 2017 by
In this contributed article, tech writer Rick Delgado, examines the differences between the terms: data science and data analytics, where people working in the tech field or other related industries probably hear these terms all the time, often interchangeably. Although they may sound similar, the terms are often quite different and have differing implications for business.
