September 04, 2019 - April 30, 2020
BASIS Independent Silicon Valley
1290 Parkmoor Ave.
San Jose, CA
Prerequisites: Basic knowledge of probability, linear algebra (feature vectors, weights, matrices), and programming ability (python is preferred)! Activity Organizer: Rahul Sharma Email: email@example.com Dates: Every 2nd and 4th Thursdays of each month Times: 4:00 PM–5:00 PM Location: Room 145 Grades: 8–12 Cost: There's an additional fee payable to the club advisor ( please contact advisor with questions) Description: Modeled after the Stanford University CS221/229 A.I. principles course, Artificial Intelligence Club is aimed at developing computer science skills in the expansive fields of Machine Learning and Deep Learning. Students will cover both theory and implementation extensively through a variety of ML/DL tutorials and seminars in the club. The first half of the year is aimed at developing the skills to work with Machine Learning algorithms and analyzing them mathematically. We will cover regression and classification, sci-kit-learn, machine learning libraries, k-means clustering, Bayes ML, k-nearest neighbors, and decision trees. Beginning in December, we will jump into Deep Learning and begin with discussing Artificial Neural Networks, Perceptron, and the math behind large networks. We will cover Convolutional Neural Networks, Deep Learning Frameworks (Tensorflow, PyTorch, and Keras), LSTMs, RNNs, Reinforcement Learning/Transfer Learning, and more. Students will also develop a final project that uses an ML or DL algorithm to successfully predict or classify a certain problem or task. Prerequisites include basic knowledge of probability, linear algebra (feature vectors, weights, matrices), and programming ability (python is preferred). Prior completion of, or concurrent enrollment in AP Statistics and AP Computer Science are recommended for this club.