Week 7: Deep Learning

Week 7: Deep Learning

Deep learning is a specialized form of machine learning that focuses on developing algorithms  and models inspired by the structure of the human brain. More specifically it is modeled after the neuron network in the brain. Deep learning models are designed to automatically learn and represent data in increasingly complex ways by using multiple layers of representations. The term deep learning can be traced back as far as the 1940's but did not regain popularity until the 2000's when it was reintroduced to the academic community.

Geoffrey Hinton, Yoshua Bengio, and Yann LeCun are researchers that have been coined the godfathers of deep learning. These individuals significantly advanced deep learning algorithms, architectures, and applications, laying the foundation for the widespread adoption of deep learning across various disciplines. The main components of deep learning are Artificial Neural Networks, Deep Neural Networks, Training Algorithms, and Unsupervised Learning. Deep learning has been applied successfully in various domains, including computer vision, natural language processing, speech recognition, and many other areas where large amounts of data are available. Deep learning has been applied successfully in various areas, including computer vision, natural language processing, speech recognition, and many other areas where large amounts of data are available.

Dr. Andrew Ng the founder of Deeplearning.ai is a highly influential researcher in AI. He has written over 200 research papers in machine learning, robotics and related fields. In 2013 he was put on a list of the 100 most influential people. He is currently an associate professor at Stanford University and was a key individual in the development of the Stanford Artificial Intelligence Lab. Dr. Andrew Ng has made learning about AI more widespread and accessible.