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4.4 35 reviews on Coursera
Sequence Models for Time Series and Natural Language Processing
This course is an introduction to sequence models and their applications, including an overview of sequence model architectures and how to handle inputs of variable length.
This course is an introduction to sequence models and their applications, including an overview of sequence model architectures and how to handle inputs of variable length.
• Predict future values of a time-series
• Classify free form text
• Address time-series and text problems with recurrent neural networks
• Choose between RNNs/LSTMs and simpler models
• Train and reuse word embeddings in text problems
You will get hands-on practice building and optimizing your own text classification and sequence models on a variety of public datasets in the labs we’ll work on together.
Prerequisites: Basic SQL, familiarity with Python and TensorFlow
4.4
74 Ratings
Free
per course
Incentives
100% online
Course 4 of 5 in the
Flexible deadlines
Advanced Level
Approx. 13 hours to complete
English
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FAQs About "Sequence Models for Time Series and Natural Language Processing"
Is the online course "Sequence Models for Time Series and Natural Language Processing" free?
Yes, "Sequence Models for Time Series and Natural Language Processing" is a free online course offered on the online classes platform Coursera
Is "Sequence Models for Time Series and Natural Language Processing" an online course worth taking?
35 students from the online classes platform Coursera have given an average rating of 4.4 to the online "Sequence Models for Time Series and Natural Language Processing" and at least 4990 have completed this online training.
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