I’ve spent the past 4 weeks focusing almost entirely on theory. This week, I’m using Chollet’s Deep Learning with Python and Géron’s Hands on Machine Learning with Scikit-Learn and Tensorflow to ramp up my skill at Tensorflow. I’ll be doing exercises…

As far as machine learning algorithms go, the k-nearest neighbors algorithm is one of the simplest to understand. If you examine the algorithm a little more closely, though, you’ll notice it’s more nuanced than is readily apparent. This week I had a chance to read up on similarity-based learning in Fundamentals of Machine Learning for Predictive Data Analytics. There are a couple topics…

As mentioned in an earlier post, for the next three months, I’ll be studying machine learning as part of the first cohort of OpenAI scholars. I’ll be working with the help of my mentor Igor Mordatch and alongside my fellow Scholars.

Among your concerns when developing a model is its accuracy. In this post, we’ll discuss techniques around managing your data that can help you better evaluate the accuracy of your model.

Yo! My name’s Ifu. I’m an OpenAI Scholar.

Convolutional neural networks (or convnets for short) are used in situations where data can be expressed as a “map” wherein the proximity between two data points indicates how related they are. An image is such a map, which is why you so often hear of convnets in the context of image analysis. If you take an image and randomly rearrange all of its pixels…