Understanding The Fundamentals Of Machine Learning And Ai For Digital Business
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Understanding the Fundamentals of Machine Learning and AI for Digital Business
"Understanding the Fundamentals of Machine Learning and AI for Digital Business" is a comprehensive guide that provides a solid foundation in the concepts and applications of machine learning and artificial intelligence. This book covers a wide range of topics, from the history and understanding of machine learning to its purpose and application in the digital business landscape. Starting with the basics, readers will gain a clear understanding of supervised learning, unsupervised learning, and reinforcement learning. They will explore evaluation methods such as accuracy, precision, recall, F1 score, and ROC-AUC, and learn how to assess the performance of machine learning models. The book delves into regression analysis, covering important techniques like polynomial regression, ridge regression, lasso regression, and vector regression. It also explores classification methods, including Naive Bayes, K-Nearest Neighbors (KNN), decision trees, random forest, and support vector machines. Readers will gain insights into clustering techniques like K-means, hierarchical clustering, and density-based clustering. They will also explore the fascinating world of deep learning, including convolutional neural networks (CNN), recurrent neural networks (RNN), long short-term memory (LSTM), and natural language processing (NLP) techniques like tokenization, stemming, and lemmatization. The book provides practical exercises throughout, allowing readers to apply their knowledge and reinforce their understanding. It covers topics such as dealing with violations of assumptions, model selection and validation, and advanced regression techniques. Ethical considerations in machine learning and AI are also addressed, highlighting the importance of responsible and ethical practices in the digital business environment. With its comprehensive coverage and practical exercises, "Understanding the Fundamentals of Machine Learning and AI for Digital Business" is an essential resource for students, professionals, and anyone interested in harnessing the power of machine learning and AI in the digital era. It offers a solid foundation in theory and practical applications, equipping readers with the skills to navigate the evolving landscape of machine learning and AI and drive digital business success.
Understanding Artificial Intelligence
This book on Artificial Intelligence (AI) explores its transformative potential for individuals and businesses. It covers AI basics and its applications across various industries, presenting AI as a foundational technology that will impact all aspects of life and the economy. The author emphasizes the need for responsible AI usage and introduces the concept of the "AI Journey" for businesses to leverage AI's potential. The second edition is updated with recent developments, including large language models like Aleph Alpha and ChatGPT, generative AI, affective computing, and ethical considerations. It also discusses open-source solutions, legal frameworks, and practical use cases. Recommended for leaders, decision-makers, students, professors, and anyone interested in understanding AI's future impact.
Artificial Intelligence Fundamentals for Business Leaders
2025 Edition. Free access to the AI Academy! The perfect guide to help non-technical business leaders understand the power of AI. Completely up to date with the latest advancements in generative AI. Part of the Byte-sized Learning AI series by Now Next Later AI, these books break down complex concepts into easily digestible pieces, providing you with a solid foundation in the fundamentals of AI. More Than a Book By purchasing this book, you will also be granted free access to the AI Academy platform. There you can view free course modules, test your knowledge through quizzes, attend webinars, and engage in discussion with other readers. You will also receive free modules and 50% discount toward the enrollment in the self-paced course of the same name and enjoy video summary lessons, instructor-graded assignments, and live sessions. A course certificate will be awarded upon successful completion. AI Academy by Now Next Later AI We are the most trusted and effective learning platform dedicated to empowering leaders with the knowledge and skills needed to harness the power of AI safely and ethically. Book and Course Learning Rubric - Chapters 1-7: Understanding of AI [11%] —Demonstrated comprehension of AI's evolution, definition, applications, and comparison with human intelligence. - Chapters 8-13: Understanding of Data and Data Management [11%] — Clear understanding of the significance of big data, and strategies for data management. - Chapters 14-29: Understanding of Machine Learning [30%] — Familiarity with machine learning algorithms, different learning types, and the key steps involved in a machine learning project. - Chapters 30-35: Understanding of Deep Learning [9%] — Understanding of deep learning, its basics, and the structure and types of neural networks. - Chapters 36-40: Understanding of Model Selection and Evaluation [9%] — Ability to select and evaluate machine learning models and utilize them for decision-making. - Chapters 41-50: Understanding of Generative AI [15%] — Detailed understanding of generative AI, its value chain, models, prompt strategies, applications, opportunities, and governance challenges. Assignment: Practical Application [15%] — Ability to apply generative AI understanding to real-world business challenges, demonstrating critical thinking and strategic planning skills.