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Artificial Intelligence with Python,Used
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New edition of the bestselling guide to artificial intelligence with Python, updated to Python 3.x, with seven new chapters that cover RNNs, AI and Big Data, fundamental use cases, chatbots, and more. Key Features Completely updated and revised to Python 3.x New chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineering Learn more about deep learning algorithms, machine learning data pipelines, and chatbots Book DescriptionArtificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications.This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data.Finally, this new edition explores various realworld scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques. What you will learn Understand what artificial intelligence, machine learning, and data science are Explore the most common artificial intelligence use cases Learn how to build a machine learning pipeline Assimilate the basics of feature selection and feature engineering Identify the differences between supervised and unsupervised learning Discover the most recent advances and tools offered for AI development in the cloud Develop automatic speech recognition systems and chatbots Apply AI algorithms to time series data Who this book is forThe intended audience for this book is Python developers who want to build realworld Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory. Table of Contents Introduction to Artificial Intelligence Fundamental Use Cases for Artificial Intelligence Machine Learning Pipelines Feature Selection and Feature Engineering Classification and Regression Using Supervised Learning Predictive Analytics with Ensemble Learning Detecting Patterns with Unsupervised Learning Building Recommender Systems Logic Programming Heuristic Search Techniques Genetic Algorithms and Genetic Programming Artificial Intelligence on the Cloud Building Games with Artificial Intelligence Building a Speech Recognizer Natural Language Processing Chatbots Sequential Data and Time Series Analysis Image Recognition Neural Networks Deep Learning with Convolutional Neural Networks Recurrent Neural Networks and Other Deep Learning Models Creating Intelligent Agents with Reinforcement Learning Artificial Intelligence and Big Data
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: How many pages does the book have? A: The book has six hundred eighteen pages. It provides a comprehensive overview of artificial intelligence concepts and applications.
- Q: What size is the book? A: The book measures nine point twenty-five inches in height, seven point five inches in width, and nine point twenty-five inches in length. These dimensions make it easy to handle and read.
- Q: What binding does this book have? A: The book is available in paperback binding. This makes it lightweight and portable for on-the-go reading.
- Q: What programming knowledge do I need to read this book? A: Basic Python programming experience is required. Familiarity with machine learning concepts will enhance your understanding of the material.
- Q: Is this book suitable for beginners? A: Yes, the book is suitable for beginners with basic Python knowledge. It introduces fundamental concepts of artificial intelligence progressively.
- Q: Are there practical applications included in the book? A: Yes, the book includes practical applications for real-world AI use cases. Readers will learn to create intelligent applications using Python.
- Q: How should I store this book? A: Store the book in a cool, dry place away from direct sunlight. This will help preserve the quality of the binding and pages.
- Q: Can I return the book if I'm not satisfied? A: Yes, you can return the book if you are not satisfied. Check the retailer's return policy for specific details.
- Q: What if the book arrives damaged? A: If the book arrives damaged, you should contact the retailer for a replacement or refund. Most retailers have policies in place for such issues.
- Q: How do I clean the book's cover? A: To clean the book's cover, use a soft cloth slightly dampened with water. Avoid using harsh chemicals that could damage the cover.
- Q: Is there a warranty for the book? A: Books typically do not come with a warranty. However, you can check with the retailer for their specific policies.
- Q: What topics are covered in the book? A: The book covers topics like machine learning pipelines, deep learning models, and AI fundamentals. It includes advanced concepts like recurrent neural networks and chatbots.
- Q: Is this book a good resource for AI developers? A: Yes, this book is an excellent resource for AI developers. It offers insights into building real-world AI applications using Python.
- Q: Does the book provide examples of AI algorithms? A: Yes, the book provides numerous examples of AI algorithms. It explains how to apply these algorithms to various scenarios.
- Q: Can I find information on natural language processing in this book? A: Yes, the book covers natural language processing extensively. It includes chapters on chatbots and speech recognition.