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Welcome to Deep Learning and Natural Language Processing Master Class.
You are inundated with text, from books, papers, blogs, tweets, news, and increasingly text from spoken utterances. Natural language processing is the area of study dedicated to the automatic manipulation of speech and text by software. It is an old ï¬eld of study, originally dominated by rule-based methods designed by linguists, then statistical methods, and, more recently, deep learning methods that show great promise in the ï¬eld.
This course is for developers that know some applied machine learning and some deep learning. Maybe you want or need to start using deep learning for text on your research project or on a project at work. This course was written to help you do that quickly and efficiently by compressing years worth of knowledge and experience into a laser-focused course of hands-on tutorials.
What natural language processing is.
What deep learning is and how it is different from other machine learning methods.
How to prepare text data for modeling.
How to develop distributed representations of text using word embedding models.
How to develop a bag-of-words models.
How to author a neural sentiment analysis model for automatically predicting the class label for a text document.
How to develop a neural language model, required for any text generating neural network.
How to design a photo captioning system to automatically generate textual descriptions of photographs.
How to develop a neural machine translation system for translating text from one language to another.
This course is a hands on-guide. It is a playbook and a workbook intended for you to learn by doing and then apply your new understanding to your own natural language projects. To get the most out of the course, I would recommend working through all the examples in each tutorial. If you watch this course like a movie you'll get little out of it.
In the applied space machine learning is programming and programming is a hands on sport.
Thank you for your interest in Deep Learning and Natural Language Processing Master Class.
Feedbacks (3)
need subtitles, sometimes finding it tough to understand