Data-Driven Education Insights

  Mollick, E. (2024). Co-Intelligence: Living and working with AI . Penguin. Author : Ethan Mollick                        Publication Year : 2024                       Publisher : Penguin General Overview of the Book The book explores the rapid advancements in artificial intelligence and their profound impact on various aspects of human life, including education, work, and creativity. Mollick divides the book into two parts: Part I focuses on the creation of "alien minds" and the challenges of aligning AI with human values, while Part II delves into the practical applications of AI in different roles. The author discusses the history of AI, highlighting the groundbreaking advancements in natural language processing and the ethical considerations surrounding AI development. Mollick emphasizes the importance of inviting AI to the table, being the human in the loop, treating AI like a person, and embracing uncertainty as key principles for effective human-AI collaboration. The

  Kelleher, J. D. (2019). Deep Learning (1st ed.) . The MIT Press Buy the book here General Overview of the Book Introduces deep learning, its applications, and how it enables data-driven decision making Explains key machine learning concepts like datasets, algorithms, functions, overfitting vs underfitting Describes how neural networks work and how they implement functions  Traces history of neural networks through three key eras: threshold logic units, multilayer perceptrons/backpropagation, and deep learning Covers specialized neural network architectures like Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) Explains processes for learning functions from data using backpropagation and gradient descent algorithms Discusses future directions for deep learning like bigger datasets, new models, hardware improvements  Examines concept of representational learning in hidden neural network layers Considers challenges around interpretability and explainability of d