Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
5 Ways To Hybridize Predictive AI And Generative AI
  Originally published in Forbes AI is in trouble. Both...
This Simple Arithmetic Can Optimize Your Main Business Operations
 Originally published in Forbes Deep down, we all know that...
Predictive AI Usually Fails Because It’s Not Usually Valuated
 Originally published in Forbes Why in the world would the...
Panic Over DeepSeek Exposes AI’s Weak Foundation On Hype
 Originally published in Forbes The story about DeepSeek has disrupted...

Left-hand

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 with the issue of which programming language might be their choice when diving into data science. This is

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...

How Pattern Recognition and Machine Learning Helps Public Safety Departments

 Originally published in StateTechMagazine, May, 2019 For today’s leading deep learning methods and technology, attend the conference and training workshops at Data Driven Government (formerly PAW Government), September 25, 2019, in Washington, DC.  The NYPD is leading...

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