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Book Review: Python Data Science Handbook

I recently had a need for a Python language resource to supplement a series of courses on Deep Learning I was evaluating that depended on this widely used language. As a long-time data science practitioner, my language of choice has been R, so I relished the opportunity to dig into Python to see first hand how the other side of the data science world did machine learning. The book I settled on was “Python Data Science Handbook: Essential Tools for Working with Data” by Jake VanderPlas.

Probing the Wisdom of Apple, Inc., Crowds Using Alternative Data Sources

In this contributed article, Anasse Bari, clinical assistant professor of computer science at New York University, and software engineer Lihao Liu, provide a detailed look at the competitive analysis they performed for four major smartphone contenders: iPhone X and 8, Samsung Galaxy Note 8, Nokia 8 and Google Pixel 2 using alternative data sources.

DialogTech Helps Businesses that Value Phone Calls Drive Growth with AI and Predictive Analytics

DialogTech, a leading provider of actionable marketing analytics for phone calls, announced the addition of a new team of data scientists to help businesses that value phone calls unlock the full power of artificial intelligence to drive growth.

IBM Unveils a New High-Powered Analytics System for Fast Access to Data Science

IBM (NYSE: IBM) announced the Integrated Analytics System, a new unified data system designed to give users fast, easy access to advanced data science capabilities and the ability to work with their data across private, public or hybrid cloud environments.

Domino Data Lab Accelerates Model Delivery on AWS

Today Domino Data Lab announced general availability of its Domino Model Delivery product. Built to run natively on Amazon Web Services (AWS), this offering makes the process of deploying highly scalable production models faster and more cost effective.

Anaconda Enterprise 5 Introduces Secure Collaboration to Amplify the Impact of Enterprise Data Scientists

Anaconda, the Python data science leader, introduced Anaconda Enterprise 5 software to help organizations respond to customers and stakeholders faster, deliver strategic insight for rapid decision-making and take advantage of cutting edge machine learning.

From the Editor’s Bookshelf: My Favorite Titles for Data Science and Machine Learning

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.

The Benefits of Having a Data Scientist Career

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

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

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.