Mendez - Machine Learning for Beginners: The Comprehensive Guide To Learn Machine Learning Effectively and Artificial Intelligence Advanced, To Expert Concepts

Machine Learning for Beginners:

The Comprehensive Guide To Learn Machine Learning Effectively and Artificial Intelligence Advanced, To Expert Concepts

By

Richard Mendez

Copyright 2019 All rights reserved.

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This book is copyright secured. This is just for individual use. You can't revise, appropriate, sell, statement, use or reword any piece of the substance inside this book without the assent of the writer or copyright proprietor. Lawful activity will be sought after in case this is penetrated.

Disclaimer Notice.

If it's not too much trouble, note the data contained inside this archive is for instructive and diversion purposes as it were. This book not proposed to fill in for clinical guidance. Kindly counsel your medical services supplier for clinical guidance and therapy.

Table of Contents

Introduction

Chapter 1: What is Machine Learning?

Definition of Machine Learning History of Machine Learning The Future of Machine Learning Application of Machine Learning

Technology Industry Agricultural Industry Medical Industry Financial Industry Marketing Industry Human Behavior Industry

Benefits of Machine Learning

Practical Examples of Everyday Use of Machine Learning

Chapter 2: Machine Learning Methods

Supervised Learning Method Unsupervised Learning Method Semi-Supervised Learning Method Reinforcement Learning Method Other Learning Methods

Chapter 3: Big Data Analysis

What is Big Data?

Why is Big Data Important? How is Big Data Used?

Applications of Big Data in Todays World Big Data Analysis Tools

Zoho Analytics Cloudera Microsoft Power BI

Oracle Analytics Cloud

Pentaho Big Data Integration and Analytics SAS Institute

Sisense Splunk Tableau

Big Data and Machine Learning

Chapter 4: Machine Learning Algorithms

What is An Algorithm?

What Are Machine Learning Algorithms?

What is the Use of Machine Learning Algorithms?

Chapter 5: K Means Clustering Algorithm

What Is the K Means Clustering Algorithm? How Does This Algorithm Work?

When Should This Algorithm be Used?

Behavioral Segmentation Inventory Categorization Sorting Sensor Measurements Detecting Bots or Anomalies

Tracking and Monitoring Classification Change

Chapter 6: Artificial Neural Networks

What Are Artificial Neural Networks? How Does They Work?

When Should They be Used?

Identification and Process Control General Game Playing

Various Forms of Recognition 3D Reconstruction

Diagnosis

Finances Filtering

Chapter 7: Decision Trees

What Are Decision Trees? How Do Decision Trees Work?

The Root Node Splitting

The Decision Node The Leaf Node Pruning

Branches

Parent and Child Nodes How the Tree Works How the Tree is Read

When Should Decision Trees be Used?

Business Decisions Government Decisions Educational Decisions Programming Decisions

Chapter 8: Nave Bayes Classifier Algorithm

What Is the Nave Bayes Classifier Algorithm? How Does This Algorithm Work?

Multinomial Nave Bayes

Bernoulli Nave Bayes Gaussian Nave Bayes

When Should This Algorithm be Used?

Filing Documents

Spam and Priority Filters

Chapter 9: Random Forests

What Are Random Forests? How Do Random Forests Work?

When Should Random Forests be Used?

Chapter 10: Apriori Algorithm

What Is the Apriori Algorithm? How Does This Algorithm Work?

When Should This Algorithm be Used?

Marketing Commerce

Statistical Analysis Companies Mechanics

Service Engineers

Chapter 11: Linear and Logistic Regression

What is Linear Regression?

Multiple Linear Regression

Ordinal Regression

Multinominal Regression Discriminant Analysis

How Does Linear Regression Work? When Should Linear Regression be Used?

Budgeting Agriculture Retail Ordering

What is Logistical Regression?

How Does Logistic Regression Work? When Should Logistic Regression be Used?

Conclusion

While numerous individuals have found out about "man-made reasoning" or AI, not as numerous individuals appear to realize what AI is. So, AI is a subfield of AI and is, much of the time, the reason for AI innovation. The objective of AI innovation is to comprehend the construction of information and fit that information into explicit models that can then be perceived and utilized by people for different applications all through life.

AI is perceived as a field of PC sciences, anyway it doesn't convey the very methodology that conventional PC sciences convey. While customary PC sciences are driven with calculations that are human-made and overseen, AI is driven by calculations that the actual gadget can gain from and develop from. Past that, they are frequently worked with a quite certain reason that empowers them to represent considerable authority in explicit spaces of "information" or capacities.

Nowadays, any individual who has utilized innovation has profited with the force of AI somehow as it has gotten incorporated into normal, regular advancements. Gadgets, for example, your phone, tablet, savvy, PC, and other keen gadgets have all been planned utilizing the force of keen innovation, or AI innovation. Everything from the face acknowledgment abilities in your telephone to oneself driving innovation in vehicles is gotten from specific types of AI innovation. It has become, and keeps on turning into, a profoundly pertinent and well-informed piece of our advanced world.

The more we keep on growing new innovations and set these new advances to work in our cutting edge society, the more we are giving AI something to do for us.

Therefore, PC researchers keep on investigating AI abilities and develop this interesting type of innovation so they can be utilized in more current and surprisingly more progressive gadgets.

In this book, Machine Learning for Beginners, I need to expand on what AI is, precisely, how it works, and why it is something that individuals need to teach themselves more on. Regardless of whether you are a PC researcher or hopeful PC researcher yourself, or on the other hand in case you are an innovation devotee, I trust that you will discover extraordinary worth in what you realize here inside this book. Inside we will cover everything to help you start to comprehend AI and it's numerous utilizations so you can foster trust in what it is that you are discussing, and finding out about, when examining AI innovation.

As you read through this book, if it's not too much trouble, note that the essential objective is to assist you with learning and comprehend AI. This specific subject is an unquestionably immense theme with an apparently interminable number of subfields and spaces of center, which are all dedicated to

various strategies for progressing or using this specific innovation. Consequently, it is basically impossible that that I might actually talk about each and every part of AI innovation in a solitary book. Nonetheless, with this central information you will actually want to take your fundamental comprehension of AI and use it to grow significantly more information in your picked space of examination, should you want to seek after AI in any capacity. Along these lines, in case you are prepared to begin, how about we start!