Deep Learning is a the basis of general artifical intelligence. At the heart of this field are ‘neural nets’, which are mathematical nodes connected in specific ways to generate desired outcomes. The ways neural nets are connected hasn’t been developed into closed-form processes yet and the desired outcome is specific. The most infamous is Alpha Go.
Andrew Ng is a professor at Stanford and CEO of DeepLearning.AI, which is on a mission to make deep learning education more accessible to the world. Ng teamed up with Coursera to share his tips, tricks, and techniques. I audited the courses in this specialization to better familiarize myself with the lesson Ng and team provide. The specialization consists of five courses: Neural Networks and Deep Learning, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization , Structuring Machine Learning Projects, Convolutional Neural Networks, Sequence Models
To apply and test my skills I have completed the course assignments. However, we are not allowed to share our code publicly. To make up for this I have created similar projects that I can share.