Treffer: Python Artificial Intelligence Projects for Beginners

Title:
Python Artificial Intelligence Projects for Beginners
Source:
2018
Publisher Information:
Packt Publishing; 2018
Document Type:
E-Ressource Electronic Resource
Availability:
Open access content. Open access content
Note:
English
Other Numbers:
ESODI oai:odilo.es:00145285
1252836990
Contributing Source:
ODILO
From OAIster®, provided by the OCLC Cooperative.
Accession Number:
edsoai.on1252836990
Database:
OAIster

Weitere Informationen

Build smart applications by implementing real-world artificial intelligence projectsKey Features Explore a variety of AI projects with Python</li> Get well-versed with different types of neural networks and popular deep learning algorithms</li> Leverage popular Python deep learning libraries for your AI projects</li></ul>Book Description Artificial Intelligence (AI) is the newest technology that’s being employed among varied businesses, industries, and sectors. Python Artificial Intelligence Projects for Beginners demonstrates AI projects in Python, covering modern techniques that make up the world of Artificial Intelligence. This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library. By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progressWhat you will learn Build a prediction model using decision trees and random forest</li> Use neural networks, decision trees, and random forests for classification</li> Detect YouTube comment spam with a bag-of-words and random forests</li> Identify handwritten mathematical symbols with convolutional neural networks</li> Revise the bird species identifier to use images</li> Learn to dete