English | 2019 | ASIN: B07T1LVFJQ | 74 Pages | PDF/EPUB/AZW3/MOBi | 13.3 MB
This guidebook is going to take some to look at Python machine learning and all of the neat things that you are able to do with it.
Machine learning is a growing field, one that a lot of programmers want to spend their on.
But even though this sounds like a complicated part of technology to work with, you will find that with the help of the Python coding language, anyone can start writing their own codes in machine learning.
This guidebook is going to take a look at all of the different topics that you need to know in order to get started with Python machine learning. Some of the topics that we will explore inside include:
The basics of machine learning
The difference between supervised and unsupervised machine learning.
Setting up your new environment in the Python language.
Data preprocessing with the help of machine learning.
How to use Python coding to help with linear regression.
Decision trees and random forests.
How to work with support vector regression problems.
Can machine learning really help with Naïve Bayes problems?
Accelerated data analysis using the Python code.
And so much more!