The Handbook of Data Science and AI

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Data Science, Big Data, and Artificial Intelligence are among the most discussed yet misunderstood concepts today. This book aims to clarify these topics and equip you with practical knowledge for application. It offers a comprehensive overview of data science applications, supported by case studies that make the concepts tangible and practical examples to guide you in simple data analysis projects. The book explores data science from multiple perspectives, emphasizing how to build data platforms and utilize data science tools and methods. It will help you articulate how to create value through these techniques, enabling organizations to make quicker decisions, reduce costs, and explore new markets. Fundamental concepts such as statistics, mathematics, and legal considerations are brought to life, complemented by case studies that demonstrate the long-term impact of data-driven insights across various industries. Key topics include: foundational mathematics for Machine Learning, covering algorithms; a range of Machine Learning frameworks from statistical methods to neural networks; Natural Language Processing techniques for extracting insights from text; Computer Vision for analyzing images and videos; modeling complex systems like COVID-19 for scenario analysis; transitioning from experimentation to production-ready data science products; and essential presentation techniques for effectively communicating results.