Teaching Time: Weekends
Position:Adjunct Professor. This adjunct professor will teach the fundamentals and contemporary usage of the Tensorflow library for deep learning capstone projects. The goal is to help students understand the graphical computational model of Tensorflow, explore the functions it has to offer, and learn how to build and structure models best suited for a deep learning project. Through the teaching, students will use Tensorflow to build models of different complexity, from simple linear/logistic regression to convolutional neural network and recurrent neural networks with LSTM to solve tasks such as word embeddings, translation, optical character recognition. Students will also learn best practices to structure a model and manage research experiments.
Tensorflow is a powerful open-source software library for machine learning developed by researchers at Google Brain. It has many pre-built functions to ease the task of building different neural networks. Tensorflow allows distribution of computation across different computers, as well as multiple CPUs and GPUs within a single machine. TensorFlow provides a Python API, as well as a less documented C++ API. For this teaching, we will be using Python.
Position Requirements: Has the practical experience with Tensorflow at work, and has MS degree in Computer Science or related major.
California Science and Technology University (CSTU) is an academic institution of post graduate learning that is located in Milpitas, and committed to provide a quality education to individuals whose goals include the development of rational, systematic, and critical thinking while striving to succeed in their chosen profession. CSTU was founded in 2011 and is licensed to operate by the BPPE of California.