Machine Learning: 2 manuscript: Machine Learning for Beginners, Machine Learning with Python

Daniel Géron

ISBN 10: 1801944016 / ISBN 13: 9781801944014

Verlag: LIGHTNING SOURCE INC, 2021

Beschreibung

Zustand: Sehr gut | Seiten: 314 | Sprache: Englisch | Produktart: Bücher.

Bestandsnummer des Verkäufers 37252450/2

Bibliografische Details

• Titel: Machine Learning: 2 manuscript: Machine Learning for Beginners, Machine Learning with Python
• Verlag: LIGHTNING SOURCE INC
• Erscheinungsjahr: 2021
• Sprache: Englisch
• ISBN-10: 1801944016
• ISBN-13: 9781801944014
• Einband: Hardcover
• Zustand: Sehr gut

Über diesen Titel

Inhaltsangabe

Do want to learn how machine learning and neural networks work quickly and simply? Do you want to know how to build a machine learning model and you have no programming skill? Do you want to get started with learning data science?

This bundle is going to guide you to the basics and the principles behind machine learning. Machine learning is an active research domain and includes several different approaches. This bundle is going to help you understand the different approaches of machine learning and neural networks. It will guide you through the steps you need to build a machine learning model.

Machine learning implies programming. This bundle will teach you Python programming. This bundle does not require any pre-programming skills. It will help to get you started in Python programming, as well as how to use Python libraries to analyze data and apply machine learning.

Overall, this bundle is a go-to guide for getting started in machine learning modeling using Python programming. Once you get through the bundle, you will be able to develop your own machine learning models using Python.

Through this bundle, you will learn:

·      Principles of machine learning

·      Types of machine learning: supervised, unsupervised, semi-supervised, and reinforcement learning

·      Advantages of each type of machine learning

·      Principle and types of neural networks

·      Steps to develop and fit artificial neural network model

·      Getting started and installing Python

·      Tools and platforms for Python programming

·      How to use pandas, NumPy and matplotlib Python libraries

·      How to develop a simple linear and logistic machine learning model

·      How to develop and train a multi-layer artificial neural network two ways: from scratch and using the Python libraries

·      When to use each type of machine learning

·      The general concept of artificial neural networks

·      Activation function in artificial neural network and to choose an activation function within an artificial neural network

·      The 5 main types of artificial neural network

·      The best function to be used to train artificial neural networks.

·      the 2 main concepts to know in the training process of the artificial neural network

·      the main variants and algorithms for the formation of an artificial neural network and a machine learning model in general.

Even if you don't have any background in machine learning and Python programming, this book will give you the tools to develop machine learning models.