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What to Ask Yourself when Hiring a Data Scientist

In this special guest feature, Aria Haghighi, VP of Data Science at Amperity, discusses several important questions to ask yourself when hiring a data scientist. Hiring data scientists is hard. They’re hard to find since there are fewer trained than can meet demand, and it’s challenging to properly interview and vet them (especially the first in your organization).

Help! My Data Scientists Can’t Write (Production) Code!

In this contributed article, Nisha Talagala, Co-founder and CTO/VP of Engineering at ParallelM, takes a hard look at productionizing machine learning code and how integrating SDLC practices with MLOps (production ML) practices certifies that all code, ML or not, is managed, tracked and executed safely.

Fast-track Application Performance and Development with Intel® Performance Libraries

Intel continues its strident efforts to refine libraries optimized to yield the utmost performance from Intel® processors. The Intel® Performance Libraries provide a large collection of prebuilt and tested, performance-optimized functions to developers. By utilizing these libraries, developers can reduce the costs and time associated with software development and maintenance, and focus efforts on their own application code.

Pumas-AI Launches Julia Language-Based Software to Advance Drug Development, Patient Care

Pumas-AI – a new company established by University of Maryland School of Pharmacy faculty members Vijay Ivaturi, PhD, assistant professor in the Department of Pharmacy Practice and Science (PPS), and Joga Gobburu, PhD, MBA, professor in PPS – is proud to announce the release of its first cutting-edge software platform for pharmaceutical researchers and clinicians. Known as Pharmaceutical Modeling and Simulation (Pumas), the software was developed through a partnership with experts at Julia Computing.

Supercharge Data Science Applications with the Intel® Distribution for Python

Intel® Distribution for Python is a distribution of commonly used packages for computation and data intensive domains, such as scientific and engineering computing, big data, and data science. With Intel® Distribution for Python you can supercharge Python applications and speed up core computational packages with this performance-oriented distribution. Professionals who can gain advantage with this product include: machine learning developers, data scientists, numerical and scientific computing developers, and HPC developers.

“Above the Trend Line” – Your Industry Rumor Central for 7/23/2019

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.

The Harvard Data Science Initiative and The MIT Press Launch the HARVARD DATA SCIENCE REVIEW

The Harvard Data Science Initiative (HDSI) and the MIT Press are pleased to announce the launch of the Harvard Data Science Review (HDSR). The multimedia platform will feature leading global thinkers in the burgeoning field of data science, making research, educational resources, and commentary accessible to academics, professionals, and the interested public. With demand for data scientists booming, HDSR will provide a centralized, authoritative, and peer-reviewed publishing community to service the growing profession.

State of Data Science, Engineering & AI Report – 2019

Our friends over at Diffbot, using the Diffbot Knowledge Graph, and in only a matter of hours, conducted the single largest survey of machine learning skills ever compiled in order to generate a clear, global picture of the machine learning workforce. All of the data contained in the “State of Data Science, Engineering & AI Report – 2019” was pulled from the company’s structured database of more than 1 trillion facts about 10 trillion entities (and growing autonomously every day).

The insideBIGDATA IMPACT 50 List for Q3 2019

The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. We’re in close contact with most of the firms making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what’s driving the success of our industry so we’re in a unique position to publish our quarterly IMPACT 50 List of the most important movers and shakers in our industry. These companies have proven their relevance by the way they’re impacting the enterprise through leading edge products and services. We’re happy to publish this evolving list of the industry’s most impactful companies!

TOP 10 insideBIGDATA Articles for June 2019

In this continuing regular feature, we give all our valued readers a monthly heads-up for the top 10 most viewed articles appearing on insideBIGDATA. We’ve heard from many of our followers that this feature will enable them to catch up with important news and features flowing across our many channels.  We’re happy to oblige! We […]