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Course
AI & ML Foundations
Published by Pearson (October 14, 2024)
ISBN-13: 9780135358122
Product Information
AI & ML Foundations demystifies the world of AI and LLMs and is a non-mathematician's and data science beginners' course on how AI algorithms work. Learn how to apply the tools of Artificial Intelligence Markup Language (AI/ML) to solve problems faster, automate processes, find hidden patterns, and accelerate your work. Get an inside look into the world of AI, through passcode terms like LLMs, ChatGPT, TensorFlow, and Pytorch, along with explanations and examples that clarify what the many underlying algorithms, such as K-Means, SVM, XG Boost, and DBSCAN can do.
Topics include how AI algorithms work, including large language models, deep learning, reinforcement learning, and unsupervised learning. You'll also see examples of how these algorithms work through intuitive live demos, use development kits such as Tensorflow, Pytorch, and Sckitlearn, and get real-world, practical hands-on examples using Python and Jupyter Notebook so you can get started with your own AI projects.
Lesson 1: An Introduction to the World of Artificial Intelligence and Machine Learning
Lesson 2: Unsupervised Learning
Lesson 3: Supervised Learning
Lesson 4: Random Forests
Lesson 5: Reinforcement Learning
Lesson 6: Deep Learning
Lesson 7: An Introduction to Large Language Models
Rob Barton is a Distinguished Engineer with Cisco. Rob has worked in the IT industry for over 27 years, the last 24 of which at Cisco. Rob Graduated from the University of British Columbia with a degree in Engineering Physics. Rob is a published author, with titles on subjects of Quality of Service (QoS), Wireless Communications, and IoT. Additionally, Rob has co-authored many peer-reviewed research papers on AI/ML and leads Cisco's academic research partnership program. Rob holds numerous patents in the areas of wireless communications, network security, cloud networking, IoT, and AI. His current areas of work include Generative AI applications to network automation and security.
Jerome Henry is a Distinguished Engineer in the Office of the Wireless CTO at Cisco. His main field of research is around optimization of clients performances in unlicensed wireless networks, which includes Machine Learning and generative AI, IoT, indoor location, QoS and privacy. Jerome has more than 20 years experience teaching technical courses in more than 15 different countries and 4 different languages, to audiences ranging from graduate degree students to technical support engineers. Jerome is a certified wireless networking expert (CWNE No. 45), CCIE, and has developed multiple courses and authored several wireless books and video courses. Jerome holds more than 300 patents, is a member of the IEEE, where he was elevated to Senior Member in 2013, and also represents Cisco with Wi-Fi Alliance working groups. He is based in Research Triangle Park, North Carolina.