Machine Learning Introduction. Class Info Office Hours –Monday:11

Important Come to class. Pay attention. Ask questions. –There are no stupid questions!! Come to my office hours Start the homework assignments early Homework in this class requires “thinking time” Read the textbook and notes –The textbook can be difficult to read: very technical
1 What algorithms can approximate functions well (and when). How does number of training examples influence accuracy. How does complexity of hypothesis representation impact it. How does noisy data influence accuracy. What are the theoretical limits of learnability. How can prior knowledge of learner help. What clues can we get from biological learning systems. How can systems alter their own representations .

NYU School of Global Public Health - Do you want to learn how to conduct data-driven COVID-19 research AND boost your statistics skill set? Sign up for these new summer 2020 Biostatistics

Introduction to Statistical Learning Why do we Need Statistical Learning?

Course: Ayahuasca Healing, Science and Indigenous Knowledge - Chacruna

MAKE, Free Full-Text

CSC 411: Introduction to Machine Learning

What is Artificial Intelligence ( AI) in 2024?- Great Learning

Introduction to feature engineering for time series forecasting, by Francesca Lazzeri, Data Science at Microsoft

Cyber Security Full course - 11 Hours, Cyber Security Training For Beginners

CSC321 Neural Networks and Machine Learning (UTM)

Artificial Intelligence and Machine Learning: Transforming Surgical Practice and Education Course