Practice - Applications in NLP (Sentiment Analysis) & Time Series Forecasting (Conceptual)
Practice Questions
Test your understanding with targeted questions
What are RNNs used for?
💡 Hint: Think about what types of input data have a sequence.
Explain sentiment analysis in simple terms.
💡 Hint: Consider how emotions can be expressed in words.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What type of network is primarily used for processing sequences?
💡 Hint: Consider which architecture is meant for remembering past inputs.
True or False: LSTMs are better than standard RNNs at learning long-term dependencies.
💡 Hint: Consider the properties of LSTMs.
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Challenge Problems
Push your limits with advanced challenges
Design a basic structure for an RNN that could be used for sentiment analysis. Outline the layers and functions you would include.
💡 Hint: Think about the flow of data through the model.
Examine a dataset to predict future stock prices. Discuss what features would be necessary to provide the RNN to enhance its predictions.
💡 Hint: Consider both historical data and external information impacting stock prices.
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Reference links
Supplementary resources to enhance your learning experience.