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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!

Algorithms: Not Evil, Helpful

INFORMS member Gah-Yi Ban of the London Business School breaks down what algorithms are and how they are useful in a unique talk at a TEDx event. She compares algorithms to evil beings and says it’s a common misconception. Ban helps people understand the role of algorithms in our present lives and how we can shape their role in our future.

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 […]

The Future of AI in Retail: Fueling Change for the Industry

In this special guest feature, Matt Field, President and Co-Founder of MakerSights, says there’s no denying that AI and ML are starting to change the nature of the retail industry. One of its greatest benefits will be in how intelligent automation can be used by humans to augment their jobs. Embracing AI and ML and incorporating this with human intuition to predict, create and manage consumer preferences can help retailers increase their bottom line while meeting modern consumer expectations for personalized, on-trend and convenient products.

Machine Learning as a Service (MLaaS) and its business implications in 2019

In this special guest feature, Rob Light, Research Principal at G2 Crowd, believes that the technology behind MLaaS will become prominent in 2019 with the help of the cloud giants, media and consulting partnership opportunities. Businesses will become more aware of the abundant opportunities these solutions present and implementations will expand, so much so that they may become the reason businesses choose specific cloud computing providers. While that may seem optimistic, it is also a very rational next step in achieving true digital transformation.

Book Review: AI Blueprints by Dr. Joshua Eckroth

Having just finished teaching a couple of introductory data science classes this past academic quarter, I came to the realization that it’s hard for newbie data scientists to get started on a project of reasonable complexity. Many students got frustrated in establishing a framework (or “blueprint”) with which to start building their machine learning applications for their class project. A new title from Packt Publishing, “AI Blueprints,” by Dr. Joshua Eckroth, helps solve this problem by laying out six real-life business scenarios for how AI can solve critical challenges with state-of-the-art AI software libraries and a well thought out workflow.

Human Guided Machine Learning is the Golden Path to Golden Records

In this special guest feature, Matt Holzapfel, Solutions Lead at Tamr, addresses how a bottom-up approach recognizes connections in the vast pools of data to identify not only the most reliable data for each entity in the ecosystem, but the means by which that data can reliably be updated — a far faster path to data mastering, and a better way to make sure that data stays golden.

Machine Learning Beyond Predefined Recipes

The next evolution in human intelligence is automating the creation of machine learning models to not follow predefined formulas, but rather adapt and evolve according to the problem’s data. While machine learning has enabled massive advancements across industries, it requires significant development and maintenance efforts from data science teams. Enter Darwin, a machine learning tool that automates the building and deployment of models at scale.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – May 2019

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.