L Intelligence Artificielle En Pratique Avec Python
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L Intelligence Artificielle En Pratique Avec Python
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Author : Hugues Bersini
language : fr
Publisher: Editions Eyrolles
Release Date : 2021-11-18
L Intelligence Artificielle En Pratique Avec Python written by Hugues Bersini and has been published by Editions Eyrolles this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-18 with Computers categories.
Un livre à la fois théorique et pratique Cet ouvrage à vocation pédagogique a pour but d’aider les débutants et même les praticiens confirmés de l’intelligence artificielle à mieux faire le tri entre certains mécanismes algorithmiques propres
L Intelligence Artificielle En Pratique Avec Python 3e Dition
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Author : Hugues Bersini
language : fr
Publisher:
Release Date : 2024-05-30
L Intelligence Artificielle En Pratique Avec Python 3e Dition written by Hugues Bersini and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-30 with categories.
L Intelligence Artificielle En Pratique Avec Python 3e Dition
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Author : Hugues Bersini
language : fr
Publisher: Editions Eyrolles
Release Date : 2024-05-30
L Intelligence Artificielle En Pratique Avec Python 3e Dition written by Hugues Bersini and has been published by Editions Eyrolles this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-30 with Computers categories.
Cet ouvrage à vocation essentiellement pédagogique a pour but d'aider les débutants et praticiens confirmés de l'Intelligence Artificielle à mieux faire le tri dans un ensemble de mécanismes algorithmiques propres à cette discipline et souvent confon
L Intelligence Artificielle En Pratique Avec Python
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Author : Hugues Bersini
language : fr
Publisher: Editions Eyrolles
Release Date : 2023-03-09
L Intelligence Artificielle En Pratique Avec Python written by Hugues Bersini and has been published by Editions Eyrolles this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-09 with Computers categories.
Un livre à la fois théorique et pratique Cet ouvrage à vocation pédagogique a pour but d’aider les débutants et même les praticiens confirmés de l’intelligence artificielle à mieux faire le tri entre certains mécanismes algorithmiques propres à cett
Intelligence Artificielle Vulgaris E
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Author : Aurélien Vannieuwenhuyze
language : fr
Publisher:
Release Date : 2019-09-05
Intelligence Artificielle Vulgaris E written by Aurélien Vannieuwenhuyze and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-05 with categories.
Intelligent Projects Using Python
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Author : Santanu Pattanayak
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-01-31
Intelligent Projects Using Python written by Santanu Pattanayak 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 2019-01-31 with Computers categories.
Implement machine learning and deep learning methodologies to build smart, cognitive AI projects using Python Key FeaturesA go-to guide to help you master AI algorithms and concepts8 real-world projects tackling different challenges in healthcare, e-commerce, and surveillanceUse TensorFlow, Keras, and other Python libraries to implement smart AI applicationsBook Description This book will be a perfect companion if you want to build insightful projects from leading AI domains using Python. The book covers detailed implementation of projects from all the core disciplines of AI. We start by covering the basics of how to create smart systems using machine learning and deep learning techniques. You will assimilate various neural network architectures such as CNN, RNN, LSTM, to solve critical new world challenges. You will learn to train a model to detect diabetic retinopathy conditions in the human eye and create an intelligent system for performing a video-to-text translation. You will use the transfer learning technique in the healthcare domain and implement style transfer using GANs. Later you will learn to build AI-based recommendation systems, a mobile app for sentiment analysis and a powerful chatbot for carrying customer services. You will implement AI techniques in the cybersecurity domain to generate Captchas. Later you will train and build autonomous vehicles to self-drive using reinforcement learning. You will be using libraries from the Python ecosystem such as TensorFlow, Keras and more to bring the core aspects of machine learning, deep learning, and AI. By the end of this book, you will be skilled to build your own smart models for tackling any kind of AI problems without any hassle. What you will learnBuild an intelligent machine translation system using seq-2-seq neural translation machinesCreate AI applications using GAN and deploy smart mobile apps using TensorFlowTranslate videos into text using CNN and RNNImplement smart AI Chatbots, and integrate and extend them in several domainsCreate smart reinforcement, learning-based applications using Q-LearningBreak and generate CAPTCHA using Deep Learning and Adversarial Learning Who this book is for This book is intended for data scientists, machine learning professionals, and deep learning practitioners who are ready to extend their knowledge and potential in AI. If you want to build real-life smart systems to play a crucial role in every complex domain, then this book is what you need. Knowledge of Python programming and a familiarity with basic machine learning and deep learning concepts are expected to help you get the most out of the book
Artificial Intelligence With Python
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Author : Alberto Artasanchez
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-01-31
Artificial Intelligence With Python written by Alberto Artasanchez 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 2020-01-31 with Computers categories.
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 FeaturesCompletely updated and revised to Python 3.xNew chapters for AI on the cloud, recurrent neural networks, deep learning models, and feature selection and engineeringLearn more about deep learning algorithms, machine learning data pipelines, and chatbotsBook Description Artificial 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 real-world 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 learnUnderstand what artificial intelligence, machine learning, and data science areExplore the most common artificial intelligence use casesLearn how to build a machine learning pipelineAssimilate the basics of feature selection and feature engineeringIdentify the differences between supervised and unsupervised learningDiscover the most recent advances and tools offered for AI development in the cloudDevelop automatic speech recognition systems and chatbotsApply AI algorithms to time series dataWho this book is for The intended audience for this book is Python developers who want to build real-world Artificial Intelligence applications. Basic Python programming experience and awareness of machine learning concepts and techniques is mandatory.
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
Artificial Intelligence Programming With Python
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Author : Perry Xiao
language : en
Publisher: John Wiley & Sons
Release Date : 2022-02-21
Artificial Intelligence Programming With Python written by Perry Xiao and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-21 with Computers categories.
A hands-on roadmap to using Python for artificial intelligence programming In Practical Artificial Intelligence Programming with Python: From Zero to Hero, veteran educator and photophysicist Dr. Perry Xiao delivers a thorough introduction to one of the most exciting areas of computer science in modern history. The book demystifies artificial intelligence and teaches readers its fundamentals from scratch in simple and plain language and with illustrative code examples. Divided into three parts, the author explains artificial intelligence generally, machine learning, and deep learning. It tackles a wide variety of useful topics, from classification and regression in machine learning to generative adversarial networks. He also includes: Fulsome introductions to MATLAB, Python, AI, machine learning, and deep learning Expansive discussions on supervised and unsupervised machine learning, as well as semi-supervised learning Practical AI and Python “cheat sheet” quick references This hands-on AI programming guide is perfect for anyone with a basic knowledge of programming—including familiarity with variables, arrays, loops, if-else statements, and file input and output—who seeks to understand foundational concepts in AI and AI development.
Explainable Ai With Python
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Author : Leonida Gianfagna
language : en
Publisher: Springer Nature
Release Date : 2021-04-28
Explainable Ai With Python written by Leonida Gianfagna and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-28 with Computers categories.
This book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches presented can be applied to almost all the current “machine learning” models: linear and logistic regression, deep learning neural networks, natural language processing and image recognition, among the others. Progress in Machine Learning is increasing the use of artificial agents to perform critical tasks previously handled by humans (healthcare, legal and finance, among others). While the principles that guide the design of these agents are understood, most of the current deep-learning models are "opaque" to human understanding. Explainable AI with Python fills the current gap in literature on this emerging topic by taking both a theoretical and a practical perspective, making the reader quickly capable of working with tools and code for Explainable AI. Beginning with examples of what Explainable AI (XAI) is and why it is needed in the field, the book details different approaches to XAI depending on specific context and need. Hands-on work on interpretable models with specific examples leveraging Python are then presented, showing how intrinsic interpretable models can be interpreted and how to produce “human understandable” explanations. Model-agnostic methods for XAI are shown to produce explanations without relying on ML models internals that are “opaque.” Using examples from Computer Vision, the authors then look at explainable models for Deep Learning and prospective methods for the future. Taking a practical perspective, the authors demonstrate how to effectively use ML and XAI in science. The final chapter explains Adversarial Machine Learning and how to do XAI with adversarial examples.