Over the past few years, deep learning has given rise to a massive collection of ideas and techniques which are disruptive to conventional machine learning practices. However, are those ideas totally different from the traditional methods? Where are the connections and differences? What are the advantages and disadvantages? How practical are the deep learning methods for business applications? Chao will share her thoughts on those questions based on her readings and hands on experiments in the areas of text analytics (question answering system, sentiment analysis) and healthcare image classification.

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Further reading about Deep Learning and Machine Learning

☞ Machine Learning A-Z™: Hands-On Python & R In Data Science

☞ Machine Learning for Front-End Developers

☞ The Future of Machine Learning and JavaScript

☞ Deep Learning With TensorFlow 2.0

☞ How to get started with Python for Deep Learning and Data Science

#deep-learning #machine-learning #data-science