In this course, we will study how to develop and apply machine learning methods to different application domains as well as efficient processing of machine learning methods. We will study state-of-the-art machine learning frameworks such as Facebook’s PyTorch or Google’s TensorFlow. We will study the basic knowledge of various machine learning models, such as logistic regression, support vector machine, and neural networks. We will also study optimization techniques such as compression and pruning to enable efficient processing of neural networks. In this course, we will thoroughly examine the emerging trends in industry to understand the underlying research challenges and opportunities. We will implement the machine learning methods and apply on real-world datasets. We will optimize the existing neural networks model using covered techniques and evaluate its effectiveness.