Title from disc surface. Course no. 9070. Includes bibliographical references (pages 176-181) in course guidebook. Lecturer: Professor Michael L. Littman, Brown University.
Contents:
Disc 3. Mastering the machine learning process. Starting with Python Notebooks and Colab -- Decision trees for logical rules -- Neural networks for perceptual rules -- Opening the Black box of neural network -- Bayesian models for probability prediction -- Genetic algorithms for evolved rules -- Disc 2. Nearest neighbors for using similarity -- The fundamental pitfall of overfitting -- Pitfalls in applying machine learning -- Clustering and semi-supervised learning -- Recommendations with three types of learning -- Games with reinforcement learning -- Disc 3. Deep learning for computer vision -- Getting a deep learner back on track -- Text categorization with words as vectors -- Deep networks that output language -- Making stylistic images with deep networks -- Making photorealistic images with GANs -- Disc 3. Deep learning for speech recognition -- Inverse reinforcement learning from people -- Casual inference comes to machine learning -- The unexpected power of over-parameterization -- Protecting privacy within machine learning -- Mastering the machine learning process.
Summary:
Learn the mechanics of machine learning with a try-it-yourself course taught by an award-winning educator and researcher.
This resource is supported by the Institute of Museum and Library Services under the provisions of the Library Services and Technology Act as administered by State Library of Iowa.