February 2017
Beginner to intermediate
1100 pages
25h 19m
English
book
Scala: Guide for Data Science Professionals
by Pascal Bugnion, Arun Manivannan, Patrick R. Nicolas
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Genetic algorithm components
Genetic algorithms have the following three components:
- Genetic encoding (and decoding): This is the conversion of a solution candidate and its components into the binary format (an array of bits or a string of
0and1characters) - Genetic operations: This is the application of a set of operators to extract the best (most genetically fit) candidates (chromosomes)
- Genetic fitness function: This is the evaluation of the fittest candidate using an objective function
Encodings and the fitness function are problem dependent. Genetic operators are not.
Encodings
Let's consider the optimization problem in machine learning that consists of maximizing the log likelihood or minimizing the loss function. The goal is to compute the parameters ...
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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.