Machine Learning Algorithms

Vadim Smolyakov
Machine Learning Algorithms in Depth

Machine Learning Algorithms in Depth dives deep into the 'how' and the 'why' of machine learning algorithms. For each category of an algorithm, you will go from math-first principles to hands-on implement…

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This book constitutes the refereed proceedings of the First International Conference on Machine Learning Algorithms, ICMLA 2024, held in Himachal Pradesh, India, during February 23¿24, 2024.The 23 full pa…

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Alvaro Rocha, Fadele Ayotunde Alaba
Malware Detection on Smart Wearables Using Machine Learning Algorithms

This book digs into the important confluence of cybersecurity and big data, providing insights into the ever-changing environment of cyber threats and solutions to protect these enormous databases. In the…

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Prashad
Optimization Algorithms for Machine Learning: Theory and Practice

In the realm of machine learning, optimization algorithms play a pivotal role in refining models for optimal performance. These algorithms, ranging from classic gradient descent to advanced techniques lik…

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Kinky
Exploring Optimization Algorithms in Machine Learning: From Theory to Practice

Optimization algorithms in machine learning bridge theoretical foundations with practical applications, crucial for refining model performance. Techniques like gradient descent, stochastic gradient descen…

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Edward Dongbo Cui
Vectorization

Enables readers to develop foundational and advanced vectorization skills for scalable data science and machine learning and address real-world problemsOffering insights across various domains such as com…

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Mazin A. M. Al Janabi
Liquidity Dynamics and Risk Modeling

This book presents a high-quality contribution to the applications of modern financial algorithms for liquidity risk management and its practical uses and applications to investable portfolios and mutual …

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Vaibhav Verdhan
Models and Algorithms for Unlabelled Data

Discover all-practical implementations of the key algorithms and models for handling unlabeled data. Full of case studies demonstrating how to apply each technique to real-world problems. In Models and Al…

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Constantin Gonciulea, Charlee Stefanski
Building Quantum Software in Python

A developer-centric look at quantum computing.The demand for developers who can implement solutions with quantum resources is growing larger every day. Building Quantum Software with Python gives you the …

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Carl Kingsford
An Introduction to String Algorithms

An essential introduction to the building blocks of modern text processingString algorithms make it possible to process, store, and manipulate text with computational efficiency, with applications ranging…

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Practical Machine Learning Tools and Techniques for Industrial Applications

The main goal of the book is to provide a comprehensive and accessible guide that empowers readers to understand, apply, and leverage machine learning algorithms and techniques effectively in real-world s…

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Jeff Edmonds
How to Think about Algorithms

"The second edition of this student-friendly textbook now includes over 150 new exercises, key concept summaries and a chapter on machine learning algorithms. Its approachability and clarity make it …

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Quantum Machine Learning

Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode …

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Maya
Innovations in Speaker State Identification: Beyond Emotion to Humor, Charisma, and More

Innovations in Speaker State Identification: Beyond Emotion to Humor, Charisma, and More explores groundbreaking advancements in identifying nuanced speaker states beyond traditional emotions. This resear…

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Azhar Ul Haque Sario
Stock Price Predictions

This comprehensive guide explores stock market prediction models, catering to both novice and seasoned investors. It provides detailed explanations of traditional and modern approaches, including Fundamen…

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Iqbal H. Sarker
AI-Driven Cybersecurity and Threat Intelligence

This book explores the dynamics of how AI (Artificial Intelligence) technology intersects with cybersecurity challenges and threat intelligence as they evolve. Integrating AI into cybersecurity not only o…

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Sunil Gupta, Sanjoy Kumar Debnath, Monit Kapoor
Artificial Intelligence-Enabled Security for Healthcare Systems

The book "AI-Enabled Healthcare Security: Safeguarding Patient Data and Improving Outcomes" focuses on the role of artificial intelligence in enhancing healthcare security and improving patient …

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Taeho Jo
Deep Learning Foundations

This book provides a conceptual understanding of deep learning algorithms. The book consists of the four parts: foundations, deep machine learning, deep neural networks, and textual deep learning. The fir…

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Cyber Malware

This book provides the foundational aspects of malware attack vectors and appropriate defense mechanisms against malware. The book equips readers with the necessary knowledge and techniques to successfull…

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Harnessing Automation and Machine Learning for Resource Recovery and Value Creation

Harnessing Automation and Machine Learning for Resource Recovery and Value Creation: From Waste to Valueprovides a comprehensive understanding of how automation and machine learning technologies can be us…

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