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What a Machine Learning Developer Should Know

This is a sponsored post by Mobilunity

Machine learning has become a massive buzzword, a term often coupled with artificial intelligence and is almost always present in talks, conferences, and events centered on technological innovations. While it’s easy to get excited about the term and get eager to dabble with the technology, any aspiring machine learning developer should first be aware of what machine learning truly entails and how it’s a driving force for recent artificial intelligence breakthroughs.

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Tricking Neural Networks: Create your own Adversarial Examples

Assassination by neural network. Sound crazy? Well, it might happen someday, and not in the way you may think. Of course neural networks could be trained to pilot drones or operate other weapons of mass destruction, but even an innocuous (and presently available) network trained to drive a car could be turned to act against its owner. This is because neural networks are extremely susceptible to something called adversarial examples.

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Machine Learning Crash Course: Part 5 - Decision Trees and Ensemble Models

Trees are great. They provide food, air, shade, and all the other good stuff we enjoy in life. Decision trees, however, are even cooler. True to their name, decision trees allow us to figure out what to do with all the great data we have in life.

Like it or not, you have been working with decision trees your entire life. When you say, “If it’s raining, I will bring an umbrella,” you’ve just constructed a simple decision tree.

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Machine Learning Crash Course: Part 4 - The Bias-Variance Dilemma

Here’s a riddle:

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ML@B's New Projects

Every semester, Machine Learning at Berkeley takes on new projects. Here’s the latest scoop on the newest projects we’ve taken on this semester.

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