First General Body Meeting
Lecturer(s): Ryan Bahlous-Boldi
At this meeting, we'll introduce the club and its goals. You'll also get to meet our officers and learn about what they do. This is a great opportunity to meet new poeple and to ensure that your suggesstions are incorporatd for the coming semster.
Introduction to Machine Learning
Lecturer(s): Ryan Bahlous-Boldi
Get a start to machine learning fundamentals, types, and various applications of machine learning in this beginner series lecture!
Link(s): Google Slides
Math of ML
Lecturer(s): Aadam Lokhandwala
Learn about fundamental mathematical concepts important to Machine Learning such as: Linear Algebra, Calculus, Backpropagation, and Gradient Optimizers.
Link(s): Echo 360 Recording, Google Colab Demo
Advanced Regression
Lecturer(s): Suryam Gupta
Dive deeper into Machine Learning mathematical concepts such as Multi-Layer Perceptrons, Nonlinear Regression, and Activation Functions.
Link(s): Google Colab Demo 1, Google Colab Demo 2
Python for ML
Lecturer(s): Karthik Shankar, Ruchira Sharma
Learn the basics of Python and how to use it for Machine Learning. More specifically, certain technologies covered are Python along with NumPy, Pandas, PyTorch, and Hugging Face.
Link(s): Echo360 Recording, Google Colab Demo
Computer Vision
Lecturer(s): Karthik Shankar, Kien To
Learn about a specific field of Machine Learning, Computer Vision, and how it is used in the real world. Technologies covered are ConvNet, Classification Loss, and other Neural Network (NN) Models
Generative Machine Learning
Lecturer(s): Suryam Gupta, Kien To
Learn more about the intricacies of Generative AI: Variational Autoencoders, and Generative Adversarial Networks.
Reinforcement Learning
Lecturer(s): Aadam Lokhandwala
Learn about the basics of RL which was invented at UMass Amherst! Specific topics are Q-Learning, Tabular Reinforcement, and Function Approximation.
Deep Reinforcement Learning
Lecturer(s): Ryan Bahlous-Boldi
Dive deeper into the previous talk on RL and learn Deep-Q Network and Proximal Policy Optimization.
Link(s): Google Colab Demo
Natural Language Processing (NLP)
Lecturer(s): Ruichira Sharma
Learn about the basics of NLP and how it is used in the real world. Specific topics are Basic NLP, Recurrent NNs (RNNs), and Long Short-Term Memory (LSTM).
Evolutionary Computation
Lecturer(s): Ryan Bahlous-Boldi
Learn about the basics of Evolutionary Computation from Ryan, a leading researcher in the field! Specific topics include: NeuroEvolution of Augmenting Topologies (NEAT), HyperNEAT, Covariance Matrix Adaptation Evolution Strategy
Recommender Systems
Lecturer(s): Kim
Ever wonder how Netflix and YouTube recommend content? This lecture is all about understanding how Information Retrieval and Recommender Systems work.