November 2018
Intermediate to advanced
322 pages
7h 54m
English
Content preview from TensorFlow Machine Learning Projects
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Understanding Adam Optimization
Before we look at Adam optimization, let's try to first understand the concept of gradient descent.
Gradient descent is an iterative optimization algorithm to find the minimum of a function. An analogous example could be as follows: let's say we are stuck on somewhere in middle of a mountain and we want to reach the ground in fastest possible manner. As a first step, we will observe the slope of mountain in all directions around us and decide to take the the direction with steepest slope down.
We re-evaluate our choice of direction after every step we take. Also, the size of our walking also depends on the steepness of the downward slope. If the slope is very steep, we take bigger steps as it can help us to ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.