Deep Learning Series, P1: Basics of Neural Networks and Understanding Gradient Descent

This post consists of the following two sections: Section 1: Basics of Neural Networks Section 2: Understanding Backward Propagation and Gradient Descent Section 1 Introduction For decades researchers have been trying to deconstruct the inner workings of our incredible and fascinating brains, hoping to learn to infuse a brain-like intelligence into machines. For example, when... Continue Reading →

How great products are made: Rules of Machine Learning by Google, a Summary

Google recently published some nuggets of ML wisdom, i.e., their best practices in ML Engineering. I believe that everyone should know about such best practices, so let's look at them. Please read the following statement a couple of times before moving on: Do machine learning like the great engineer you are, not like the great... Continue Reading →

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