Pytorch Artificial Intelligence Fundamentals
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Pytorch Artificial Intelligence Fundamentals
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Author : Jibin Mathew
language : en
Publisher:
Release Date : 2020-02-28
Pytorch Artificial Intelligence Fundamentals written by Jibin Mathew and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-28 with Computers categories.
Artificial Intelligence Fundamentals Asq S Pocket Guide
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Author : Jayet Moon
language : en
Publisher: Quality Press
Release Date : 2025-04-15
Artificial Intelligence Fundamentals Asq S Pocket Guide written by Jayet Moon and has been published by Quality Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-15 with Computers categories.
How is understanding artificial intelligence (AI) and machine learning (ML) useful to a quality professional? The answer may surprise you. With Artificial Intelligence Fundamentals, you’ll learn how these new technologies can be integrated into everyday quality management practices to make your work faster, efficient, scalable, and more effective. Author Jayet Moon covers a wide range of topics, including working with ChatGPT, successfully using AI for problem solving, and following best practices.
Pytorch Essentials A Comprehensive Guide To Machine Learning Techniques
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Author : Adam Jones
language : en
Publisher: Walzone Press
Release Date : 2024-12-03
Pytorch Essentials A Comprehensive Guide To Machine Learning Techniques written by Adam Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-03 with Computers categories.
"PyTorch Essentials: A Comprehensive Guide to Machine Learning Techniques" is an essential resource for programmers, researchers, and enthusiasts eager to enhance their mastery of machine learning and artificial intelligence through the PyTorch framework. This guide deftly combines theoretical foundations with hands-on applications, covering everything from basic tensor manipulation and neural network creation to sophisticated architectures such as CNNs, RNNs, and generative models. Additionally, it delves into reinforcement learning, optimization strategies, and best practices for deployment, empowering readers with the skills to develop scalable, production-ready solutions. Whether advancing your research or solving real-world industry challenges, this book serves as your indispensable guide to mastering machine learning with PyTorch.
Kickstart Artificial Intelligence Fundamentals
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Author : Dr. S.Mahesh Anand
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2025-03-29
Kickstart Artificial Intelligence Fundamentals written by Dr. S.Mahesh Anand and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-29 with Computers categories.
TAGLINE Master AI Fundamentals and Build Real-World Machine Learning and Deep Learning Solutions KEY FEATURES ● Hands-on AI guide with Python, TensorFlow, and Keras implementations. ● Step-by-step walkthroughs of Machine Learning, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM) models. ● Bridges AI theory with real-world applications and coding exercises. DESCRIPTION AI is transforming industries, driving innovation, and shaping the future of technology. A strong foundation in AI fundamentals is essential for anyone looking to stay ahead in this rapidly evolving field. Kickstart Artificial Intelligence Fundamentals is a comprehensive companion designed to demystify core AI concepts, covering Machine Learning, Deep Learning, and Neural Networks. Tailored for all AI enthusiasts, this book provides hands-on Python implementation using the TensorFlow-Keras framework, ensuring a seamless learning experience from theory to practice. Bridging the gap between concepts and real-world applications, this book offers intuitive explanations, mathematical foundations, and practical use cases. Readers will explore supervised and unsupervised Machine Learning models, master Convolutional Neural Networks for image classification, and leverage Long Short-Term Memory networks for time-series forecasting. Each chapter includes coding examples and guided exercises, making it an invaluable resource for both beginners and advanced learners. Beyond technical expertise, this book explores emerging trends like Generative AI and ethical considerations in AI, preparing readers for the challenges and opportunities in the field. This book will provide you the essential knowledge and hands-on experience to stay competitive. Don’t get left behind—embrace AI and future-proof your career today! WHAT WILL YOU LEARN ● Build and train machine learning models for real-world datasets. ● Apply neural networks to classification and regression tasks. ● Implement CNNs and LSTMs for vision and sequence modeling. ● Solve AI problems using Python, TensorFlow, and Keras. ● Fine-tune pre-trained models for domain-specific applications. ● Explore generative AI for creative and industrial use cases. WHO IS THIS BOOK FOR? This book is tailored for students in AI courses at leading universities and professionals transitioning into AI. Suitable for undergraduates in BE, BTech, BCA, MCA, and related fields, as well as data scientists, software engineers, and analysts, it bridges AI theory with hands-on Python applications. Whether you're a beginner or an expert, this guide equips you with essential AI and GenAI skills. TABLE OF CONTENTS 1. Introduction and Evolution of AI Technologies 2. Modern Approach to AI 3. Introduction to Machine Learning 4. Regression Versus Classification Model 5. Naive Bayes as a Linear Classifier 6. Tree-Based Machine Learning Models 7. Distance-Based Machine Learning Models 8. Support Vector Machines 9. Introduction to Artificial Neural Networks 10. Training Neural Networks 11. Introduction to Convolutional Neural Networks 12. Classification Using CNN 13. Pre-trained CNN Architectures 14. Introduction to Recurrent Neural Networks 15. Introduction to Long Short-Term Memory (LSTM) 16. Application of LSTM in NLP and TS Forecasting 17. Emerging Trends and Ethical Considerations in AI Index
Pytorch Pocket Reference
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Author : Joe Papa
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-05-11
Pytorch Pocket Reference written by Joe Papa and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-11 with Computers categories.
This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips. Author Joe Papa provides instant access to syntax, design patterns, and code examples to accelerate your development and reduce the time you spend searching for answers. Research scientists, machine learning engineers, and software developers will find clear, structured PyTorch code that covers every step of neural network development-from loading data to customizing training loops to model optimization and GPU/TPU acceleration. Quickly learn how to deploy your code to production using AWS, Google Cloud, or Azure and deploy your ML models to mobile and edge devices. Learn basic PyTorch syntax and design patterns Create custom models and data transforms Train and deploy models using a GPU and TPU Train and test a deep learning classifier Accelerate training using optimization and distributed training Access useful PyTorch libraries and the PyTorch ecosystem
Understanding Artificial Intelligence
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Author : Albert Chun-Chen Liu
language : en
Publisher: John Wiley & Sons
Release Date : 2022-08-31
Understanding Artificial Intelligence written by Albert Chun-Chen Liu 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 2022-08-31 with Computers categories.
Understanding Artificial Intelligence Provides students across majors with a clear and accessible overview of new artificial intelligence technologies and applications Artificial intelligence (AI) is broadly defined as computers programmed to simulate the cognitive functions of the human mind. In combination with the Neural Network (NN), Big Data (BD), and the Internet of Things (IoT), artificial intelligence has transformed everyday life: self-driving cars, delivery drones, digital assistants, facial recognition devices, autonomous vacuum cleaners, and mobile navigation apps all rely on AI to perform tasks. With the rise of artificial intelligence, the job market of the near future will be radically different???many jobs will disappear, yet new jobs and opportunities will emerge. Understanding Artificial Intelligence: Fundamentals and Applications covers the fundamental concepts and key technologies of AI while exploring its impact on the future of work. Requiring no previous background in artificial intelligence, this easy-to-understand textbook addresses AI challenges in healthcare, finance, retail, manufacturing, agriculture, government, and smart city development. Each chapter includes simple computer laboratories to teach students how to develop artificial intelligence applications and integrate software and hardware for robotic development. In addition, this text: Focuses on artificial intelligence applications in different industries and sectors Traces the history of neural networks and explains popular neural network architectures Covers AI technologies, such as Machine Vision (MV), Natural Language Processing (NLP), and Unmanned Aerial Vehicles (UAV) Describes various artificial intelligence computational platforms, including Google Tensor Processing Unit (TPU) and Kneron Neural Processing Unit (NPU) Highlights the development of new artificial intelligence hardware and architectures Understanding Artificial Intelligence: Fundamentals and Applications is an excellent textbook for undergraduates in business, humanities, the arts, science, healthcare, engineering, and many other disciplines. It is also an invaluable guide for working professionals wanting to learn about the ways AI is changing their particular field.
The The Deep Learning With Pytorch Workshop
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Author : Hyatt Saleh
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-07-22
The The Deep Learning With Pytorch Workshop written by Hyatt Saleh 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 2020-07-22 with Computers categories.
Get a head start in the world of AI and deep learning by developing your skills with PyTorch Key FeaturesLearn how to define your own network architecture in deep learningImplement helpful methods to create and train a model using PyTorch syntaxDiscover how intelligent applications using features like image recognition and speech recognition really process your dataBook Description Want to get to grips with one of the most popular machine learning libraries for deep learning? The Deep Learning with PyTorch Workshop will help you do just that, jumpstarting your knowledge of using PyTorch for deep learning even if you’re starting from scratch. It's no surprise that deep learning's popularity has risen steeply in the past few years, thanks to intelligent applications such as self-driving vehicles, chatbots, and voice-activated assistants that are making our lives easier. This book will take you inside the world of deep learning, where you'll use PyTorch to understand the complexity of neural network architectures. The Deep Learning with PyTorch Workshop starts with an introduction to deep learning and its applications. You'll explore the syntax of PyTorch and learn how to define a network architecture and train a model. Next, you'll learn about three main neural network architectures - convolutional, artificial, and recurrent - and even solve real-world data problems using these networks. Later chapters will show you how to create a style transfer model to develop a new image from two images, before finally taking you through how RNNs store memory to solve key data issues. By the end of this book, you'll have mastered the essential concepts, tools, and libraries of PyTorch to develop your own deep neural networks and intelligent apps. What you will learnExplore the different applications of deep learningUnderstand the PyTorch approach to building neural networksCreate and train your very own perceptron using PyTorchSolve regression problems using artificial neural networks (ANNs)Handle computer vision problems with convolutional neural networks (CNNs)Perform language translation tasks using recurrent neural networks (RNNs)Who this book is for This deep learning book is ideal for anyone who wants to create and train deep learning models using PyTorch. A solid understanding of the Python programming language and its packages will help you grasp the topics covered in the book more quickly.
Fundamentals Of Artificial Intelligence Machine Learning
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Author : Dr. Shoieb Ahamed
language : en
Publisher: Academic Guru Publishing House
Release Date : 2023-10-13
Fundamentals Of Artificial Intelligence Machine Learning written by Dr. Shoieb Ahamed and has been published by Academic Guru Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-13 with Study Aids categories.
We have been curious in teaching computers to learn ever since they were first developed. The implications would be enormous if we knew how to teach them, via programming, to learn and improve automatically with use. Think of personal software assistants that learn their users’ changing interests and then highlight the stories from the online morning newspaper that are most relevant to them based on that information; computers that learn from medical records which treatments are best for new diseases; homes that learn to optimise energy costs based on the unique usage patterns of their occupants. If we could figure out how to teach machines, it would pave the way for all sorts of advanced computing applications and individualised experiences. Human learning skills (and shortcomings) may be better understood with a deeper knowledge of information processing methods for machine learning. Within the recent decade, “machine learning” and “artificial intelligence” have been widely used in a variety of settings. Both phrases are widely used in the scientific and media communities, often with overlapping but not always synonymous meanings. The authors of this book set out to define the terminologies at play here and, more specifically, to outline the role that machine learning plays in AI. The authors provide a literature analysis and a conceptual framework that explain how machine learning contributes to the development of (artificial) intelligent agents.
Hands On Artificial Intelligence For Banking
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Author : Jeffrey Ng
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-07-10
Hands On Artificial Intelligence For Banking written by Jeffrey Ng 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 2020-07-10 with Computers categories.
Delve into the world of real-world financial applications using deep learning, artificial intelligence, and production-grade data feeds and technology with Python Key FeaturesUnderstand how to obtain financial data via Quandl or internal systemsAutomate commercial banking using artificial intelligence and Python programsImplement various artificial intelligence models to make personal banking easyBook Description Remodeling your outlook on banking begins with keeping up to date with the latest and most effective approaches, such as artificial intelligence (AI). Hands-On Artificial Intelligence for Banking is a practical guide that will help you advance in your career in the banking domain. The book will demonstrate AI implementation to make your banking services smoother, more cost-efficient, and accessible to clients, focusing on both the client- and server-side uses of AI. You’ll begin by understanding the importance of artificial intelligence, while also gaining insights into the recent AI revolution in the banking industry. Next, you’ll get hands-on machine learning experience, exploring how to use time series analysis and reinforcement learning to automate client procurements and banking and finance decisions. After this, you’ll progress to learning about mechanizing capital market decisions, using automated portfolio management systems and predicting the future of investment banking. In addition to this, you’ll explore concepts such as building personal wealth advisors and mass customization of client lifetime wealth. Finally, you’ll get to grips with some real-world AI considerations in the field of banking. By the end of this book, you’ll be equipped with the skills you need to navigate the finance domain by leveraging the power of AI. What you will learnAutomate commercial bank pricing with reinforcement learningPerform technical analysis using convolutional layers in KerasUse natural language processing (NLP) for predicting market responses and visualizing them using graph databasesDeploy a robot advisor to manage your personal finances via Open Bank APISense market needs using sentiment analysis for algorithmic marketingExplore AI adoption in banking using practical examplesUnderstand how to obtain financial data from commercial, open, and internal sourcesWho this book is for This is one of the most useful artificial intelligence books for machine learning engineers, data engineers, and data scientists working in the finance industry who are looking to implement AI in their business applications. The book will also help entrepreneurs, venture capitalists, investment bankers, and wealth managers who want to understand the importance of AI in finance and banking and how it can help them solve different problems related to these domains. Prior experience in the financial markets or banking domain, and working knowledge of the Python programming language are a must.
Exploring Artificial Intelligence A Student S Handbook
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Author : Dr Thiyagarajan Sivaprakasam
language : en
Publisher: THIYAGARAJAN SIVAPRAKASAM
Release Date : 2024-05-15
Exploring Artificial Intelligence A Student S Handbook written by Dr Thiyagarajan Sivaprakasam and has been published by THIYAGARAJAN SIVAPRAKASAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-15 with Computers categories.
Exploring Artificial intelligence: A Student’s Handbook is a comprehensive educational guide designed to demystify Al for students, covering foundational theories and practical applications across twenty chapters. It progresses from basic machine learning algorithms to advanced topics, incorporating interactive quizzes, “Did You Know?” facts, and real-world examples to enrich learning. The book emphasizes hands-on interaction with Al through step-by-step activities, aiming to bridge theory and practice. It also addresses the ethical, societal, and futuristic aspects of Al, encouraging readers to consider the broader implications of Al technologies. This handbook serves as a foundational resource for aspiring Al enthusiasts, researchers, and practitioners, fostering a deeper understanding of Al’s impact on the future.