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6THINTERNATIONAL ENGINEERING AND TECHNOLOGY MANAGEMENT SUMMIT 2024
The 6th INTERNATIONAL ENGINEERING AND TECHNOLOGY MANAGEMENT SUMMIT (ETMS 2024), organized by Başkent University, was held in Ankara, Türkiye, from October 17-19, 2024. This year’s theme, “Engineering and Technology Management in Defense Industry,” provided a critical platform for discussing the challenges and opportunities in this rapidly evolving field. ETMS 2024 brought together researchers, professionals, and industry leaders to explore topics such as advanced weapon systems, surveillance technologies, and strategic infrastructure management. The summit examined the societal and environmental impacts of defense technologies while fostering innovative strategies to address emerging...
Introduction to Machine Learning with Python
Many Python developers are curious about what machine learning is and how it can be concretely applied to solve issues faced in businesses handling medium to large amount of data. Machine Learning with Python teaches you the basics of machine learning and provides a thorough hands-on understanding of the subject.You'll learn important machine learning concepts and algorithms, when to use them, and how to use them. The book will cover a machine learning workflow: data preprocessing and working with data, training algorithms, evaluating results, and implementing those algorithms into a production-level system.
Data Analysis
In the ever-evolving landscape of business, data analysis has emerged as a powerful tool for decision-making, innovation, and competitive advantage. This book delves into the intricacies of data analysis and its practical applications in the corporate realm. Embark on a journey through the world of data analysis, exploring its fundamental concepts, methodologies, and real-world applications. Unveiling the Power of Data Analysis In this comprehensive guide, we delve into the fundamental principles of data analysis, enabling you to harness the power of data to drive business success. We begin by defining data analysis and its multifaceted role in business operations. Next, we embark on a journ...
Python for Data Analysis
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the ...
SPIN
From the concert stage to the dressing room, from the recording studio to the digital realm, SPIN surveys the modern musical landscape and the culture around it with authoritative reporting, provocative interviews, and a discerning critical ear. With dynamic photography, bold graphic design, and informed irreverence, the pages of SPIN pulsate with the energy of today's most innovative sounds. Whether covering what's new or what's next, SPIN is your monthly VIP pass to all that rocks.
Introduction to Machine Learning with Python
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with t...
Introduction to Machine Learning with Python
Machine learning is a subfield of artificial intelligence, broadly defined as a machine's capability to imitate intelligent human behavior. Like humans, machines become capable of making intelligent decisions by learning from their past experiences. Machine learning is being employed in many applications, including fraud detection and prevention, self-driving cars, recommendation systems, facial recognition technology, and intelligent computing. This book helps beginners learn the art and science of machine learning. It presens real-world examples that leverage the popular Python machine learning ecosystem, The topics covered in this book include machine learning basics: supervised and unsup...
Machine and Deep Learning Algorithms and Applications
This book introduces basic machine learning concepts and applications for a broad audience that includes students, faculty, and industry practitioners. We begin by describing how machine learning provides capabilities to computers and embedded systems to learn from data. A typical machine learning algorithm involves training, and generally the performance of a machine learning model improves with more training data. Deep learning is a sub-area of machine learning that involves extensive use of layers of artificial neural networks typically trained on massive amounts of data. Machine and deep learning methods are often used in contemporary data science tasks to address the growing data sets a...
ESSENTIALS OF AI AND SOFT COMPUTING
The book has been primarily designed for the beginners in the subject. It has been written from the students' perspective, making it easy to understand. The contents are briefly explained with the help of examples in a direct and a pragmatic approach. Each chapter begins with the basics and is standalone; the dependence of the chapters on previous concepts has been minimized. The text is aimed to balance the mix of notation and words in mathematical statements. Artificial Intelligence and Soft Computing topics are often expressed in terms of algorithms, hence key algorithms are introduced with their explanations. These algorithms are expressed in words and in an easy to understand form of st...
AI-Powered Productivity
AI-Powered Productivity is a guide to understanding and using AI and generative tools in professional settings. Chapter 1 introduces AI basics, its impact on various sectors, and an overview of generative AI tools. Chapter 2 delves into large language models exploring their integration with multimodal technologies and effects on productivity. Chapter 3 offers a practical guide to mastering LLM prompting and customization, with tutorials on crafting effective prompts and advanced techniques, including real-world examples of AI applications. Chapter 4 examines how AI can enhance individual productivity, focusing on professional and personal benefits, ethical use, and future trends. Chapter 5 a...
