Deep Learning with Python and Keras: Build a Model For Sentiment Analysis
Deep Learning with Python and Keras: Build a Model For Sentiment Analysis
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 55m | 206 MB
Instructor: Janani Ravi
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 55m | 206 MB
Instructor: Janani Ravi
Learn to apply sentiment analysis to your problems through a practical, real world use case. In this course, certified Google cloud architect and data engineer Janani Ravi guides you through the process of building and training a RNN to do sentiment analysis, including validating your results.
Go over how to preprocess text for sentiment analysis, as well as approaches you can use and challenges you may encounter. Get set up with Google Colab and import Python modules and loading data, then learn how to analyze word lengths, clean and preprocess text, and visualize text with word clouds. Explore feed-forward neural networks, then dive into configuring, training, and evaluating your dense neural network (DNN). Plus, learn how to train RNNs and LSTNs.
Deep Learning with Python and Keras: Build a Model For Sentiment Analysis
