Predictive Analytics Times
Predictive Analytics Times
EXCLUSIVE HIGHLIGHTS
Interview: The Institute of Business Forecasting & Planning Talks to Dr. Eric Siegel
  Dr. Eric Siegel cuts through the buzzwords surrounding...
Investment Modeling Grounded In Data Science
 For more from Dr. Elder, join Predictive Analytics World...
Some Thoughts On Being a Data Science Entrepreneur in a Disruptive Economy
 The movie “Being There” may seem like an odd...
Asking the Right Analytics Questions and Whether Tiger Woods is better than Jack Nicklaus
  One of the most fundamental contributions we can...

Left-hand

Data Lakes: The Future of Data Warehousing?

 Originally published in InsideBigData, August 2, 2019. The term Big Data has been around since 2005, but what does it actually mean? Exactly how big is big? We are creating data every second. It’s generated across all industries and by myriad devices, from computers to industrial sensors to weather balloons and countless other sources. According

10 Great Python Resources for Aspiring Data Scientists

  Originally published in KDNuggets, September 10, 2019 Python is one of the most widely used languages in data science, and an incredibly popular general programming language on its own. Many prospective data scientists are first faced...

Machine Learning You Can Dance To

  Originally published in MIT News, September 18, 2019. Rhythmic flashes from a computer screen illuminate a dark room as sounds fill the air. The snare drum sample comes out crisp and clean by itself, but turns...

Top 10 Data Science Use Cases in Energy and Utilities

 Originally published in KDNuggets, September, 2019. The energy sector is under constant development, and more of significant inventions and innovations are yet to come. The energy use has always been involved in other industries like agriculture, manufacturing,...

Machine Learning in Auditing – Current and Future Applications

  Originally published in The CPA Journal, June, 2019. Machine learning is a key subset of artificial intelligence (AI), which originated with the idea that machines could be taught to learn in ways similar to how humans...

An Easy Introduction to Machine Learning Recommender Systems

  Originally published in KDNuggets, September, 2019. Recommender systems are an important class of machine learning algorithms that offer “relevant” suggestions to users. Categorized as either collaborative filtering or a content-based system, check out how these approaches...

What Happened to Hadoop? And Where Do We Go from Here?

 Originally published by InsideBigData, September 4, 2019. Apache Hadoop emerged on the IT scene in 2006 with the promise to provide organizations with the capability to store an unprecedented volume of data using cheap, commodity hardware. In...

The Death of Big Data and the Emergence of the Multi-Cloud Era

 Originally published in KDnuggets, July, 2019 The Era of Big Data is coming to an end as the focus shifts from how we collect data to processing that data in real-time. Big Data is now a business...

12 Things I Learned During My First Year as a Machine Learning Engineer

 Originally published in Towards Data Science, July 6, 2019 Being your own biggest sceptic, the value in trying things which might not work and why communication problems are harder than technical problems. Machine learning and data science...

From Foodie Pic to Your Plate: Generating Recipes With Facebook AI

  Originally published in Synced, June 20, 2019 Imagine snapping a pic of your tasty restaurant entree or the magnificent lasagna in a foodie post, and up pops a recipe for said dish. Facebook AI has now...

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