| Description
| The goal of this course is to introduce the SOTA deep learning approaches and allow students to develop deep learning applications using Python programming-based deep learning libraries (TensorFlow & Keras). The course content includes: 1. related deep learning algorithms comprising Convolutional Neural Networks (CNNs), Long-Short Term Memory (LSTM), Generative Adversarial Networks (GANs) and Deep Reinforcement Learning, 2. License plate/Doorplate Recognition, 3. Face Recognition, 4. Image Classification, 5. Object Detection, 6. Autonomous vehicles and autopilot simulations and applications, and 7. Embedded deep learning algorithms.
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