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Machine Learning is a subfield within Artificial Intelligence that builds algorithms that allow computers to learn to perform tasks from data instead of being explicitly programmed.
Machine learning works spectacularly well, but mathematicians aren’t quite sure why.
Building and training your first TensorFlow graph from the ground up.
This is the first of a multi-part series explaining the fundamentals of deep learning by long-time tech journalist Michael Copeland.
When you’re browsing sites like Netflix or Amazon, you get recommendations on what to watch or buy next. This is actually a big deal, and companies offer huge prizes to make these algorithms better.
Most firms that thinks they want advanced AI/ML really just need linear regression on cleaned-up data.
After years of studying your social media behavior, here are 5 predictions machine learning can make about you and your community from your public feed.
You can use Machine Learning as a service using different cloud API offerings today. We will look at Azure Machine Learning Studio to start with.To go over these in detail, we will go ahead and build a movie recommendation service using the movielens dataset.
We will build our own handwritten text recognition model, convert it to a CoreML model and use it in a native iOS app to detect handwritten numbers — OFFLINE!
Answers to the three most commonly asked questions about maintaining GDPR-compliant machine learning programs.
Logistic regression is a simple classification method which is widely used in the field of machine learning. Today we’re going to talk about how to train our own logistic regression model in Python to build a a binary classifier. We’ll use NumPy for matrix operations, SciPy for cost minimization, Matplotlib for data visualization and no machine learning tools or libraries whatsoever.
ML.NET is an open-source and cross-platform framework and available as NuGet package. It was originally developed in Microsoft Research and it is used across many Microsoft products like Windows, Bing, Azure, etc. One very cool thing about this framework is that it can be extended to add machine learning libraries like TensorFlow, Accord.NET, and CNTK.
A visual prank exposes an Achilles’ heel of computer vision systems: Unlike humans, they can’t do a double take.