Learn the most modern techniques for supervised learning, used in common applications such as facial recognition, speech recognition, and self driving cars. This course will also provide students with a linux server with GPU acceleration to run their algorithms. Topics include regression, test classification, convolutional image recognition, and more.
- This course gives students access to professional research grade hardware, including compute servers such as a 16 core server with 128GB RAM, terabytes of fast storage, and research grade graphics processors such as the Titan X Pascal GPU
- This course also teaches students how to use linux tools and the CUDA + GPU accelerated python research environment, using Tensorflow-GPU 1.4, Keras 2.1.4 - tools compiled with lubcudnn 6 and 7
- Course material draws from recent academic research published in the last 2-5 years, including deep networks, single shot detection, convolutional or vectorizated models for language, as well as (time permitting) demo projects featuring AlphaZero Go and GAN inspired sequence to sequence learning.
This course no longer uses Theano, and students will model primarily with the Keras deep learning library backed by Tensorflow.
Completion of CS01b or AP CS, or permission of instructor. Also requires Algebra II math experience. CS82 highly recommended but not required.
Kids Coding Sample Projects
These are examples of projects that students create as they grow their skills in CS84
Post-Undergraduate / Research Grade Tools, Modeling with Keras and Tensorflow
Cutting edge techniques from resesarch in the last 2-5 years, e.g. Deep Convolutional Networks and Object Detection / Localization
GPU Compute Resources for Class include Titan Xp, GTX 1080ti, 32 Virtual Core Machine with 128GB RAM
Word Vectorization, Natural Language Classification, and broad coverage of different types of data sets
Linux tools, compute servers, provided in class. Students learn how to ask the right questions and perform research independently
Independent Student Projects can be submitted to science fairs or continued on in CS85
* Office Hours Included. See time on the bottom of website.
** Instructors currently scheduled are not guaranteed and could change at KTBYTE's discretion