Artificial Intelligence With Python
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Artificial Intelligence With Python
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Author : Teik Toe Teoh
language : en
Publisher: Springer Nature
Release Date : 2022-03-16
Artificial Intelligence With Python written by Teik Toe Teoh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-16 with Computers categories.
Entering the field of artificial intelligence and data science can seem daunting to beginners with little to no prior background, especially those with no programming experience. The concepts used in self-driving cars and virtual assistants like Amazon’s Alexa may seem very complex and difficult to grasp. The aim of Artificial Intelligence in Python is to make AI accessible and easy to understand for people with little to no programming experience though practical exercises. Newcomers will gain the necessary knowledge on how to create such systems, which are capable of executing tasks that require some form of human-like intelligence. This book introduces readers to various topics and examples of programming in Python, as well as key concepts in artificial intelligence. Python programming skills will be imparted as we go along. Concepts and code snippets will be covered in a step-by-step manner, to guide and instill confidence in beginners. Complex subjects in deep learning and machine learning will be broken down into easy-to-digest content and examples. Artificial intelligence implementations will also be shared, allowing beginners to generate their own artificial intelligence algorithms for reinforcement learning, style transfer, chatbots, speech, and natural language processing.
Machine Learning With Python
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Author : Russel R Russo
language : en
Publisher:
Release Date : 2021-02-04
Machine Learning With Python written by Russel R Russo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-04 with categories.
Are you fascinated by Machine Learning but it seems too complicated?Do you have some coding skills but you want to go deeper in Python and Machine Learning? If this is you, please keep reading: you are in the right place, looking at the right book. Since you are reading this you are probably aware of how important Artificial Intelligence is in these days. In your everyday life Artificial Intelligence is all around you. Every time you buy a product on Amazon, follow a new profile on Instagram, listen to a song on Spotify or reserve a room on Booking, they are learning something out of your behavior. And these are just the most visible aspects of how Machine Learning is having an impact on our lives. Everyone knows (well, almost everyone) how important Machine Learning is for the growth and success of the biggest tech companies, and many people know about the Machine Learning impact in science, medicine and statistics. Also, it is quite commonly known that Artificial Intelligence, Machine Learning, and the mastering of their most important language, Python, can offer a lot of possibilities in work and business. And you yourself are probably thinking "I surely can see that opportunity, but how can I seize it?" Well, if you kept reading so far you are on the right track to answer your question. In Machine Learning with Python you will find: Why python is the best language for Machine Learning How to bring your ideas into a computer The smartest way to approach Machine Learning How to deal with variables and data Tips and tricks for a smooth and painless journey into artificial intelligence The most common myths about Machine Learning debunked So, whether you decided to start now or to go deeper into Artificial Intelligence, Machine Learning and Python Programming, you will only have two unanswered questions right now: "what is the best way to do it? And when is the best time to start?" An easy, clear and complete guide as Machine Learning with Python is the answer to your first question, and about the second one, well, that's an easy one: the best time is NOW! Buy Machine Learning with Python now and start mastering the secrets of Artificial Intelligence.
Ai With Python For Beginners
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Author : Jim Smith
language : en
Publisher:
Release Date : 2019-07-30
Ai With Python For Beginners written by Jim Smith and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-30 with categories.
AI With PythonSince the invention of computers or machines, their capability to perform various tasks has experienced an exponential growth. Humans have developed the power of computer systems in terms of their diverse working domains, their increasing speed, and reducing size with respect to time.A branch of Computer Science named Artificial Intelligence pursues creating the computers or machines as intelligent as human beings.Artificial intelligence's progress is staggering. Efforts to advance AI concepts over the past 20 years have resulted in some truly amazing innovations. Big data, medical research, and autonomous vehicles are just some of the incredible applications emerging from AI development.This book covers the basic concepts of various fields of artificial intelligence like Artificial Neural Networks, Natural Language Processing, Machine Learning, Deep Learning, Genetic algorithms etc., and its implementation in Python.What You Will Learn: -Introduction-Machine Learning-Data Preparations-Supervised Learning-Logic Programming-Clustering-Natural Language Processing-Time Series Data-Speech Recognition-Heuristic Search-Gaming-Much, Much More!
Python Ai Programming
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Author : Patrick J
language : en
Publisher: GitforGits
Release Date : 2024-01-03
Python Ai Programming written by Patrick J and has been published by GitforGits this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-03 with Computers categories.
This book aspires young graduates and programmers to become AI engineers and enter the world of artificial intelligence by combining powerful Python programming with artificial intelligence. Beginning with the fundamentals of Python programming, the book gradually progresses to machine learning, where readers learn to implement Python in developing predictive models. The book provides a clear and accessible explanation of machine learning, incorporating practical examples and exercises that strengthen understanding. We go deep into deep learning, another vital component of AI. Readers gain a thorough understanding of how Python's frameworks and libraries can be used to create sophisticated neural networks and algorithms, which are required for tasks such as image and speech recognition. Natural Language Processing is also covered in the book, with fundamental concepts and techniques for interpreting and generating human-like language covered. The book's focus on computer vision and reinforcement learning is distinctive, presenting these cutting-edge AI fields in an approachable manner. Readers will learn how to use Python's intuitive programming paradigm to create systems that interpret visual data and make intelligent decisions based on environmental interactions. The book focuses on ethical AI development and responsible programming, emphasizing the importance of developing AI that is fair, transparent, and accountable. Each chapter is designed to improve learning by including practical examples, case studies, and exercises that provide hands-on experience. This book is an excellent starting point for anyone interested in becoming an AI engineer, providing the necessary foundational knowledge and skills to delve into the fascinating world of artificial intelligence. Key Learnings Explore Python basics and AI integration for real-world application and career advancement. Experience the power of Python in AI with practical machine learning techniques. Practice Python's deep learning tools for innovative AI solution development. Dive into NLP with Python to revolutionize data interpretation and communication strategies. Simple yet practical understanding of reinforcement learning for strategic AI decision making. Uncover ethical AI development and frameworks, and concepts of responsible and trustworthy AI. Harness Python's capabilities for creating AI applications with a focus on fairness and bias. Table of Content Introduction to Artificial Intelligence Python for AI Data as Fuel for AI Machine Learning Foundation Essentials of Deep Learning NLP and Computer Vision Hands-on Reinforcement Learning Ethics to AI
Python
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Author : Giuseppe Bonaccorso
language : en
Publisher:
Release Date : 2018-12-19
Python written by Giuseppe Bonaccorso and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-19 with Computers categories.
Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problems Key Features Master supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for object detection, image classification, similarity learning, and more Build, deploy, and scale end-to-end deep neural network models in a production environment Book Description This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems This Learning Path includes content from the following Packt products: Mastering Machine Learning Algorithms by Giuseppe Bonaccorso Mastering TensorFlow 1.x by Armando Fandango Deep Learning for Computer Vision by Rajalingappaa Shanmugamani What you will learn Explore how an ML model can be trained, optimized, and evaluated Work with Autoencoders and Generative Adversarial Networks Explore the most important Reinforcement Learning techniques Build end-to-end deep learning (CNN, RNN, and Autoencoders) models Who this book is for This Learning Path is for data scientists, machine learning engineers, artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. You will encounter the advanced intricacies and complex use cases of deep learning and AI. A basic knowledge of programming in Python and some understanding of machine learning concepts are required to get the best out of this Learning Path.
Artificial Intelligence Python
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Author : Anthony S. Williams
language : en
Publisher: Anthony S. Williams
Release Date : 2020-10-31
Artificial Intelligence Python written by Anthony S. Williams and has been published by Anthony S. Williams this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-31 with Computers categories.
Artificial Intelligence With Python It is more than apparent that artificial intelligence techniques and practices will navigate the changes in the near future and simply shape the world. It is fair to say that AP is leading approach when it comes to the various scientific fields as well as various industries and today, it is almost impossible the world without advancements in the artificial intelligence field. Experts and scientists both agree that artificial intelligence is the field which will most certainly shape our economic future, automotive industry, health care, cybersecurity as well as cybercrime. Over the coming decades, AI will greatly impact every aspect of our lives including our work, careers, education, care for elderly and much more. Eventually, it will alter the world completely, as machines will pursue complex goals independently of their creators. AI tools have become mainstream tools when it comes to the various industries and science fields since these tools greatly reduce costs, increase profits and even save lives. If you understand the basic concept behind different AI techniques and approaches, you will be able to greatly benefit from it in various aspects. In order to maximise the benefits of AI advancements, you have to be ready to embark on different challenges. However, with this book, you will be able to overcome challenges and the reward is a success. What you will learn in this book: Different artificial intelligence approaches and goals How to define AI system Basic AI techniques Reinforcement learning How to build a recommender system Genetic and logic programming And much, much more... Download this book NOW and learn more about Artificial Intelligence With Python!
Explainable Ai With Python
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Author : Antonio Di Cecco
language : en
Publisher: Springer Nature
Release Date : 2025-08-04
Explainable Ai With Python written by Antonio Di Cecco and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-04 with Computers categories.
This comprehensive book on Explainable Artificial Intelligence has been updated and expanded to reflect the latest advancements in the field of XAI, enriching the existing literature with new research, case studies, and practical techniques. The Second Edition expands on its predecessor by addressing advancements in AI, including large language models and multimodal systems that integrate text, visual, auditory, and sensor data. It emphasizes making complex systems interpretable without sacrificing performance and provides an enhanced focus on additive models for improved interpretability. Balancing technical rigor with accessibility, the book combines theory and practical application to equip readers with the skills needed to apply explainable AI (XAI) methods effectively in real-world contexts. Features: Expansion of the "Intrinsic Explainable Models" chapter to delve deeper into generalized additive models and other intrinsic techniques, enriching the chapter with new examples and use cases for a better understanding of intrinsic XAI models. Further details in "Model-Agnostic Methods for XAI" focused on how explanations differ between the training set and the test set, including a new model to illustrate these differences more clearly and effectively. New section in "Making Science with Machine Learning and XAI" presenting a visual approach to learning the basic functions in XAI, making the concept more accessible to readers through an interactive and engaging interface. Revision in "Adversarial Machine Learning and Explainability" that includes a code review to enhance understanding and effectiveness of the concepts discussed, ensuring that code examples are up-to-date and optimized for current best practices. New chapter on "Generative Models and Large Language Models (LLM)" chapter dedicated to generative models and large language models, exploring their role in XAI and how they can be used to create richer, more interactive explanations. This chapter also covers the explainability of transformer models and privacy through generative models. New "Artificial General Intelligence and XAI" mini-chapter dedicated to exploring the implications of Artificial General Intelligence (AGI) for XAI, discussing how advancements towards AGI systems influence strategies and methodologies for XAI. Enhancements in "Explaining Deep Learning Models" features new methodologies in explaining deep learning models, further enriching the chapter with cutting-edge techniques and insights for deeper understanding.
Beginners Artificial Intelligence And Python Programming
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Author : Olubayo Adekanmbi
language : en
Publisher:
Release Date : 2020-02-29
Beginners Artificial Intelligence And Python Programming written by Olubayo Adekanmbi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-29 with categories.
The book demystifies the concept of Artificial Intelligence (AI) in a friendly manner to kids, with the goal of stimulating their curiosity and driving their interest in learning about AI. After the generic introductions to the core concepts like machine learning, deep learning and reinforcement learning, the students are guided into step-by-step programming with Python. The intention is to transit beyond the traditional code-first approach to understanding broad concepts that will sufficiently motivate a desire to learn coding.The book is useful to any beginner, kids or adult, who desires to build basic knowledge in the general concept of Artificial Intelligence
Python Artificial Intelligence Projects For Beginners
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Author : Dr. Joshua Eckroth
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-07-31
Python Artificial Intelligence Projects For Beginners written by Dr. Joshua Eckroth and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-31 with Computers categories.
Build smart applications by implementing real-world artificial intelligence projects Key Features Explore a variety of AI projects with Python Get well-versed with different types of neural networks and popular deep learning algorithms Leverage popular Python deep learning libraries for your AI projects 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 progress What you will learn Build a prediction model using decision trees and random forest Use neural networks, decision trees, and random forests for classification Detect YouTube comment spam with a bag-of-words and random forests Identify handwritten mathematical symbols with convolutional neural networks Revise the bird species identifier to use images Learn to detect positive and negative sentiment in user reviews Who this book is for Python Artificial Intelligence Projects for Beginners is for Python developers who want to take their first step into the world of Artificial Intelligence using easy-to-follow projects. Basic working knowledge of Python programming is expected so that you’re able to play around with code
Machine Learning With Python
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Author : Mark Coding
language : en
Publisher:
Release Date : 2020-11-27
Machine Learning With Python written by Mark Coding and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-27 with Computers categories.
Are you tired of taking risks, hoping things will pay off big but you are always worried about the risks? Have you been hearing about some of the buzzwords in the world of business like data science, data analysis, and machine learning, but worry they will be too hard for you to catch onto and learn more about? Are you looking for ways to know more about your industry, what products to release, and how to gain a competitive edge overall, without all of the risks? If this sounds like something you have dealt with, then machine learning for Python is the best option for you! This guidebook is going to dive into all of the parts of this that you need to know right now! Inside, we will explore what machine learning is all about, how to add it into Python, and so many of the algorithms and steps you need to really make all of this a reality for your needs. Inside this guidebook, be prepared to take some of the basics of Python and machine learning, and turn yourself into an expert, someone who knows with certainty that all of your decisions are the right ones, and who has data and information to back them all up. Some of the different topics we will discuss in this guidebook to help make this a reality, and to ensure we can learn and make good predictions, includes: -The basics of machine learning and artificial intelligence. -How to work with Python and machine learning to get started with all the options that work with this topic. -How to work with some of the different Python machine learning algorithms out there for you to choose from. -How to work with a model of machine learning and go through the process of having your computer learn on its own. -More examples of how to work with Python and machine learning together. -The importance of working with neural networks and what all of this can mean to your code. -A look at deep learning and data science that can take your machine learning to the next level. -The steps you need to know to get started with data Preprocessing. -A look at where machine learning and more will be able to help lead us to the future. Working with machine learning for Python is an important topic a lot of businesses are diving into now more than ever. They see the value of working with data science, and what this process can do for them in terms of their success and their sound business decisions. When you are ready to learn how to use machine learning for Python for some of your business and data science needs, make sure to take a look at this guidebook to get started