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skill track

Deep Learning for NLP in Python

Further your Natural Language Processing (NLP) skills and master the machine learning techniques needed to extract insights from data. In this track, you'll learn how to create Recurrent Neural Networks (RNN), build models to translate language, and autocomplete sentences like Gmail using neural translation and seq2seq models. Through interactive exercises, you'll use the scikit-learn, TensorFlow, Keras, and NLTK libraries. Then, you’ll apply your skills to real-world data, including scripts from The Big Bang Theory, English and French vocabulary, and the works of Shakespeare. Start this track and gain the machine learning skills you need to enhance your NLP skills in Python. This track will be archived on October 28, 2022. To continue making progress on the courses in this track after this date, please enroll in the Natural Language Processing in Python or Deep Learning in Python skill tracks.

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1
Python
Recurrent Neural Networks (RNN) for Language Modeling in Python

Use RNNs to classify text sentiment, generate sentences, and translate text between languages.

4 hours

David Cecchini Headshot

David Cecchini

Data Scientist

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