Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
The Rise Of Large Database Models
 Originally published in Forbes Even as large language models have...
3 Predictions For Predictive AI In 2025
 Originally published in Forbes GenAI’s complementary sibling, predictive AI, makes...
The Quant’s Dilemma: Subjectivity In Predictive AI’s Value
 Originally published in Forbes This is the third of a...
To Deploy Predictive AI, You Must Navigate These Tradeoffs
 Originally published in Forbes This is the second of a...

Community

LinkedIn’s Fastest-Growing Jobs Today Are In Data Science and Machine Learning

 Originally published in FORBES, December 11, 2017 For today’s leading machine learning methods and technology, attend the conference and training workshops at Predictive Analytics World, June 3-7, 2018. Machine Learning Engineers, Data Scientists, and Big Data Engineers rank among the top emerging jobs on LinkedIn. Data scientist roles have grown over 650% since 2012, but currently,

Deep Learning and Google Street View Can Predict Neighborhood Politics from Parked Cars

 For more on deep learning, consider attending the inaugural Deep Learning World, June 3-7 2018 in Las Vegas. Proposals to speak currently also being accepted. Originally published in IEEE Spectrum It’s likely that your car says something about you. The...

How Adversarial Attacks Work

 Originally published in ycombinator.com Recent studies by Google Brain have shown that any machine learning classifier can be tricked to give incorrect predictions, and with a little bit of skill, you can get them to give pretty much any result...

Deep Learning vs. Machine Learning: A Data Scientist’s Perspective

 By: Rajendra Originally published in Houseofbots.com As artificial intelligence (AI) works its way into mainstream business practices, various different applications are coming up in conversations about how to best leverage the technology. In observing these conversations, I...

The Business of Artificial Intelligence—What It Can and Cannot Do for Your Organization

 Originally published in Harvard Business Review For more than 250 years the fundamental drivers of economic growth have been technological innovations. The most important of these are what economists call general-purpose technologies — a category that includes...

How Google is Remaking Itself as a “Machine Learning First” Company

  Originally published in Wired.com Carson Holgate is training to become a ninja. Not in the martial arts — she’s already done that. Holgate, 26, holds a second degree black belt in Tae Kwon Do. This time it’s...

The AI “Gaydar” Study and the Real Dangers of Big Data

 Originally published in The New Yorker Editor’s note: Keep in mind that the high “accuracies” such as 81%, as reported by this research up front, are misleading. The model is effective, with a lift around 7 at...

Using Machine Learning to Predict Value of Homes On Airbnb

 Originally published in Medium Introduction Data products have always been an instrumental part of Airbnb’s service. However, we have long recognized that it’s costly to make data products. For example, personalized search ranking enables guests to more...

Women Flocking to Statistics, the Newly Hot, High-Tech Field of Data Science

  Originally published in The Washington Post LINCOLN, Neb. — The numbers of women in science and technology are dismal: Barely 18 percent of computer science degrees go to women. Women make up 11 percent of math faculty....

How HBO’s Silicon Valley Built “Not Hotdog” with Mobile TensorFlow, Keras & React Native

 Originally published in Hacker Noon, June 26, 2017 The HBO show Silicon Valley released a real AI app that identifies hotdogs — and not hotdogs — like the one shown on season 4’s 4th episode (the app is now available on Android as well as...

Page 36 of 87 1 31 32 33 34 35 36 37 38 39 40 41 87