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English | 2021 | ASIN : B09CN2F35T | 215 pages | PDF, AZW3, EPUB, MOBI | 11.93 MB
you interested in learning data science with Python? Do you want to know what you need to get started? Then you have picked up the right guide.
As more and more data becomes available and accessible, we need to find bigger and better ways of processing it. That's where data science comes in. It is the future of AI, and that makes it important to understand, if not learn. It's also important to understand the value data science can add to businesses, and by the end of this guide, you will know what it is, how it works, and how it can use data to extract meaningful, valuable insights.
Here's what you will learn:
The difference between data analysis, data science, and machine learning
The implications and potential of data science
How to get your data and process it
What feature selection is
Data sources
How to use data visualization with matDescriptionlib
The difference between supervised, unsupervised, and reinforcement learning
What simple and multiple linear regression is
A look at decision trees and random forests
What classification is, including logistic regression and K-Nearest Neighbors
Decision tree and random forest classification
A discussion on clustering
A deeper look into reinforcement learning and how it works
A brief look at artificial neural networks
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