Название: The Python Interview Handbook 2023 : Your Ultimate Guide to Crack Any Python Interview with 500 Q & A
Автор: Nezir Zahirovic
Издательство: Leanpub
Год: 2023-06-09
Страниц: 250
Язык: английский
Формат: pdf
Размер: 25.1 MB

If you're looking for a comprehensive guide to prepare for Python interviews, The Python Interview Handbook 2023 is the perfect resource for you. This book is a must-read for anyone who wants to excel in Python interviews, and it covers more than 500 interview questions and answers about Python. Python has been one of the most popular programming languages in recent years, and it has become an essential skill for software developers, data scientists, and machine learning engineers. However, getting a job in these fields requires more than just knowing the basics of Python. You need to demonstrate your knowledge, skills, and expertise in Python during the interview process. If you're looking for a comprehensive guide to prepare for Python interviews, The Python Interview Handbook 2023 is the perfect resource for you. This book is a must-read for anyone who wants to excel in Python interviews, and it covers more than 500 interview questions and answers about Python, testing, deployment, machine learning, microservices, code samples, architecture, databases, algorithms, and more.

Название: Machine Learning in Python for Dynamic Process Systems: A practitioner’s guide for building process modeling, predictive, and monitoring solutions using dynamic data
Автор: Ankur Kumar, Jesus Flores-Cerrillo
Издательство: Leanpub
Год: June 2023
Страниц: 208
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

This book provides a comprehensive coverage of Machine Learning (ML) methods that have proven useful in process industry for dynamic process modeling. Step-by-step instructions, supported with industry-relevant case studies, show (using Python) how to develop solutions for process modeling, process monitoring, etc., using classical and modern methods. This book is designed to help readers gain a working-level knowledge of machine learning-based dynamic process modeling techniques that have proven useful in process industry. Readers can leverage the concepts learned to build advanced solutions for process monitoring, soft sensing, inferential modeling, predictive maintenance, and process control for dynamic systems. The application-focused approach of the book is reader friendly and easily digestible to the practicing and aspiring process engineers, and data scientists. No prior experience with Machine Learning or Python is needed. Undergraduate-level knowledge of basic linear algebra and calculus is assumed.

Название: Attention Augmented Learning Machines: Theory and Applications
Автор: Guoqiang Zhong, Jinxuan Sun
Издательство: Nova Science Publishers, Inc.
Год: 2023
Страниц: 140
Язык: английский
Формат: pdf (true)
Размер: 35.6 MB

Deep Learning has developed for more than 10 years. Many novel models are proposed. Among others, the attention models have greatly impacted the Deep Learning area. Similar to the attention mechanism of human beings, the attention mechanism improves the performance of many Deep Learning models based on its discovery of important information hidden in data and motivates the emergence of many new Deep Learning models, like Transformer and its variants. This book includes eight chapters and aims to introduce some interesting works on the attention mechanism. Chapter 1 is a review of the attention mechanism used in the Deep Learning area, while Chapters 2 and 3 present two models that integrate the attention mechanism into gated recurrent units (GRUs) and long short-term memory (LSTM), respectively, making them pay attention to important information in the sequences. This book can be used by college students (undergraduate or graduate) chosen to major in Computer Science, Artificial Intelligence, electrical engineering, and mathematics, or others who study or have the potential to use Deep Learning algorithms. It could be of special interest to professors who research pattern recognition, Machine Learning, computer vision, neural language processing (NLP), and related fields, or engineers who apply Deep Learning models to their products. On the other hand, the reader is assumed to be already familiar with basic computer programming, Machine Learning, pattern recognition, and computer vision.

Название: x64 Assembly Language Step-by-Step: Programming with Linux (Tech Today), 4th Edition
Автор: Jeff Duntemann
Издательство: Wiley
Год: 2024
Страниц: 636
Язык: английский
Формат: pdf (true), epub (true)
Размер: 10.5 MB, 13.0 MB

The long-awaited x64 edition of the bestselling introduction to Intel assembly language. In the newly revised fourth edition of x64 Assembly Language Step-by-Step: Programming with Linux, author Jeff Duntemann delivers an extensively rewritten introduction to assembly language with a strong focus on 64-bit long-mode Linux assembler. The book offers a lighthearted, robust, and accessible approach to a challenging technical discipline, giving you a step-by-step path to learning assembly code that's engaging and easy to read. x64 Assembly Language Step-by-Step makes quick work of programmable computing basics, the concepts of binary and hexadecimal number systems, the Intel x86/x64 computer architecture, and the process of Linux software development to dive deep into the x64 instruction set, memory addressing, procedures, macros, and interface to the C-language code libraries on which Linux is built. A one-stop resource for aspiring and practicing Intel assembly programmers, the latest edition of this celebrated text provides readers with an authoritative tutorial approach to x64 technology that's ideal for self-paced instruction.

Название: Gradient Expectations: Structure, Origins, and Synthesis of Predictive Neural Networks
Автор: Keith L. Downing
Издательство: The MIT Press
Год: 2023
Страниц: 224
Язык: английский
Формат: epub (true)
Размер: 15.4 MB

An insightful investigation into the mechanisms underlying the predictive functions of neural networks—and their ability to chart a new path for AI. Prediction is a cognitive advantage like few others, inherently linked to our ability to survive and thrive. Our brains are awash in signals that embody prediction. Can we extend this capability more explicitly into synthetic neural networks to improve the function of AI and enhance its place in our world? Gradient Expectations is a bold effort by Keith L. Downing to map the origins and anatomy of natural and artificial neural networks to explore how, when designed as predictive modules, their components might serve as the basis for the simulated evolution of advanced neural network systems. Downing delves into the known neural architecture of the mammalian brain to illuminate the structure of predictive networks and determine more precisely how the ability to predict might have evolved from more primitive neural circuits. He then surveys past and present computational neural models that leverage predictive mechanisms with biological plausibility, identifying elements, such as gradients, that natural and artificial networks share. Behind well-founded predictions lie gradients, Downing finds, but of a different scope than those that belong to today’s Deep Learning.

Название: Facilitating Professional Scrum Teams: Improve Team Alignment, Effectiveness and Outcomes (Early Release)
Автор: Patricia Kong, Glaudia Califano, David Spinks
Издательство: Addison-Wesley Professional/Pearson
Год: 2023
Страниц: 157
Язык: английский
Формат: epub, mobi
Размер: 14.1 MB

Unlock the true power of collaboration within Scrum Teams with this practical guide packed with tips, tools, and real-life scenarios to elevate your facilitation skills. Scrum requires healthy collaboration, not just between the members of the Scrum Team, but also between the Scrum Team and its stakeholders to gather feedback and input. These stakeholders include users and customers of the product developed by the Scrum Team. Collaboration is the heart of thriving Scrum Teams, but most available resources on collaboration focus solely on meeting formats and neglect to show how Scrum Teams truly harmonize their efforts and make informed decisions effectively. We offer many facilitation techniques and ideas in this book. Keep in mind that we believe an empirical approach should apply to the techniques. Once you understand the purpose of the techniques, feel free to get creative and adapt them where you see fit to help you facilitate in a way that gets the most valuable outcomes for your context. This book bridges the gap by not only providing effective facilitation techniques but also delving into the how and why of facilitationall geared toward improving effectiveness, achieving impactful outcomes, and helping Scrum Teams work through challenges.

Название: Deep Learning: Theory, Architectures and Applications in Speech, Image and Language Processing
Автор: Gyanendra Verma, Rajesh Doriya
Издательство: Bentham Books
Год: 2023
Страниц: 270
Язык: английский
Формат: pdf (true), epub
Размер: 37.6 MB

This book is a detailed reference guide on Deep Learning and its applications. It aims to provide a basic understanding of Deep Learning and its different architectures that are applied to process images, speech, and natural language. It explains basic concepts and many modern use cases through fifteen chapters contributed by Computer Science academics and researchers. By the end of the book, the reader will become familiar with different Deep Learning approaches and models, and understand how to implement various deep learning algorithms using multiple frameworks and libraries. Machine Learning proved its usefulness in many applications in the domain of Image Processing and Computer Vision, Medical Imaging, Satellite imaging, Remote Sensing, Surveillance, etc ., over the past decade. At the same time, Machine Learning methods themselves have evolved, particularly Deep Learning methods that have demonstrated significant performance over traditional Machine Learning algorithms.

Название: Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies and Applications
Автор: Abhishek Majumder, Joy Lal Sarkar, Arindam Majumder
Издательство: Bentham Books
Год: 2023
Страниц: 319
Язык: английский
Формат: pdf (true), epub
Размер: 45.8 MB

Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies and Applications captures the state of the art in usage of artificial intelligence in different types of recommendation systems and predictive analysis. The book provides guidelines and case studies for application of artificial intelligence in recommendation from expert researchers and practitioners. A detailed analysis of the relevant theoretical and practical aspects, current trends and future directions is presented. A recommendation System is an intelligent computer-based system that serves as a guide and suggests, as per the preferences of the person. It uses state-of-the-art technologies like Big Data, Machine Learning, Artificial Intelligence, etc., and benefits both the consumer and the merchant. Recommendation System is becoming very popular as it serves as a guide for the activity that a person or a group plans to perform in the best possible manner, given the constraints imposed by the user(s). Software tools and techniques provide advice on items to be used by a user.

Название: Advanced Mathematical Applications in Data Science
Автор: Biswadip Basu Mallik, Kirti Verma, Rahul Kar, Ashok Kumar Shaw
Издательство: Bentham Books
Год: 2023
Страниц: 223
Язык: английский
Формат: pdf (true), epub
Размер: 27.1 MB

Advanced Mathematical Applications in Data Science comprehensively explores the crucial role mathematics plays in the field of Data Science. Each chapter is contributed by scientists, researchers, and academicians. The 13 chapters cover a range of mathematical concepts utilized in Data Science, enabling readers to understand the intricate connection between mathematics and data analysis. The book covers diverse topics, including, Machine Learning models, the Kalman filter, data modeling, artificial neural networks, clustering techniques, and more, showcasing the application of advanced mathematical tools for effective data processing and analysis. With a strong emphasis on real-world applications, the book offers a deeper understanding of the foundational principles behind data analysis and its numerous interdisciplinary applications. This reference is an invaluable resource for graduate students, researchers, academicians, and learners pursuing a research career in mathematical computing or completing advanced data science courses. An Artificial Neural Network (ANN) is a data processing paradigm inspired by the way organic nervous systems, such as the brain, process data.

Название: Numerical Machine Learning
Автор: Zhiyuan Wang, Sayed Ameenuddin Irfan, Christopher Teoh
Издательство: Bentham Books
Год: 2023
Страниц: 225
Язык: английский
Формат: pdf (true), epub
Размер: 32.3 MB

Numerical Machine Learning is a simple textbook on machine learning that bridges the gap between mathematics theory and practice. The book uses numerical examples with small datasets and simple Python codes to provide a complete walkthrough of the underlying mathematical steps of seven commonly used machine learning algorithms and techniques, including linear regression, regularization, logistic regression, decision trees, gradient boosting, Support Vector Machine, and K-means Clustering. Through a step-by-step exploration of concrete numerical examples, the students (primarily undergraduate and graduate students studying machine learning) can develop a well-rounded understanding of these algorithms, gain an in-depth knowledge of how the mathematics relates to the implementation and performance of the algorithms, and be better equipped to apply them to practical problems. From our experiences of teaching Machine Learning using various textbooks, we have noticed that there tends to be a strong emphasis on abstract mathematics when discussing the theories of Machine Learning algorithms. On the other hand, in the application of Machine Learning, it usually straightaway goes to import offthe- shelf libraries such as scikit-learn, TensorFlow, Keras, and PyTorch.