Artificial Intelligence and Machine Learning Fundamentals
Develop real-world applications powered by the latest AI advances
Seiten
2018
Packt Publishing Limited (Verlag)
9781789801651 (ISBN)
Packt Publishing Limited (Verlag)
9781789801651 (ISBN)
Artificial Intelligence and Machine Learning Fundamentals teaches you machine learning and neural networks from the ground up using real-world examples. After you complete this book, you will be excited to revamp your current projects or build new intelligent networks.
Create AI applications in Python and lay the foundations for your career in data science
Key Features
Practical examples that explain key machine learning algorithms
Explore neural networks in detail with interesting examples
Master core AI concepts with engaging activities
Book DescriptionMachine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples.
As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law.
By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills!
What you will learn
Understand the importance, principles, and fields of AI
Implement basic artificial intelligence concepts with Python
Apply regression and classification concepts to real-world problems
Perform predictive analysis using decision trees and random forests
Carry out clustering using the k-means and mean shift algorithms
Understand the fundamentals of deep learning via practical examples
Who this book is forArtificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it’s recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).
Create AI applications in Python and lay the foundations for your career in data science
Key Features
Practical examples that explain key machine learning algorithms
Explore neural networks in detail with interesting examples
Master core AI concepts with engaging activities
Book DescriptionMachine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples.
As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law.
By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills!
What you will learn
Understand the importance, principles, and fields of AI
Implement basic artificial intelligence concepts with Python
Apply regression and classification concepts to real-world problems
Perform predictive analysis using decision trees and random forests
Carry out clustering using the k-means and mean shift algorithms
Understand the fundamentals of deep learning via practical examples
Who this book is forArtificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it’s recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).
Zsolt Nagy is an engineering manager in an ad tech company heavy on data science. After acquiring his MSc in inference on ontologies, he used AI mainly for analyzing online poker strategies to aid professional poker players in decision making. After the poker boom ended, he put extra effort into building a T-shaped profile in leadership and software engineering.
Table of Contents
Principles of Artificial Intelligence
AI with Search Techniques and Games
Regression
Classification
Using Trees for Predictive Analysis
Clustering
Deep Learning with Neural Networks
| Erscheinungsdatum | 18.12.2018 |
|---|---|
| Verlagsort | Birmingham |
| Sprache | englisch |
| Maße | 75 x 93 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| ISBN-13 | 9781789801651 / 9781789801651 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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