Description
This course teaches you step by step on how tp build iOS question answering application. It explores the world of machine learning from application developer's perspective. It explains the world of word embeddings which is fundamental technology behind text processing. As Andrew Ng has said AI is new electricity. The course highlight difference among AI (Artificial Intelligence, Machine learning and deep learning. It also teaches few embedding technologies like glove, word2vec and BERT. BERT is state of art transformer model developed by Google and has proven to be equivalent of CNN in computer vision technology. This course uses pretrained BERT model and explains how to use it in IOS question answering app. The students once armed with this knowledge will be able to demonstrate their command on machine learning and can use this technology for several different apps. The author assumes that the student does not have any background in machine learning. The course is structured as followsApp Preview: Shows preview of app that we are going to buildEmbeddings: Explains what word embeddings are and why are they importantDeep Neural Network: It covers fundamentals of deep learning, and multi layer perceptronBERT, Glove, Word2Vec: Popular word embedding technologiesBuild UI from scratch: Shows how to build UI by using basic controls in iOS swiftStep by Step Coding: Each function is explained in details with step by step walkthrough of the codeText to Speech and Speech to text: This sections explains how to use test to speech and speech top text conversion libraries in iOS app so that user can speak question into the app and hear the answer. This is extremely useful for physically challenged users who can not type using keyboardRun the app on iPhone: Shows the flow of the app on the phone.
