{"id":9405,"date":"2026-08-10T10:07:06","date_gmt":"2026-08-10T10:07:06","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/linkedin-deep-learning-with-python-and-keras-build-a-model-for-sentiment-analysis-2024-2\/"},"modified":"2026-08-10T10:07:06","modified_gmt":"2026-08-10T10:07:06","slug":"linkedin-deep-learning-with-python-and-keras-build-a-model-for-sentiment-analysis-2024-2","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/linkedin-deep-learning-with-python-and-keras-build-a-model-for-sentiment-analysis-2024-2\/","title":{"rendered":"LinkedIn \u2013 Deep Learning with Python and Keras: Build a Model For Sentiment Analysis 2024-2"},"content":{"rendered":"
\n

Description<\/span><\/h2>\n

Deep Learning with Python and Keras: Build a Model For Sentiment Analysis. This course introduces you to how to implement sentiment analysis in your projects by providing a practical and real-world example. In this course, Janani Ravi, a data engineer and cloud architect at Google, walks you through building and training a recurrent neural network (RNN) for sentiment analysis. In this course, you will learn how to prepare text for sentiment analysis, learn about potential challenges, and explore different solutions. First, you will set up the Google Colab environment and call the required Python modules and data. Then, you will learn about sentence length analysis, text cleaning and preprocessing, and data visualization using word clouds. Next, you will explore simple feedforward neural networks and go through the steps of configuring, training, and evaluating a dense neural network (DNN). You will also learn practical training methods for recurrent neural networks (RNN) and long short-term memories (LSTM). This course will help you build efficient models for processing text data with a deeper understanding of sentiment analysis and deep learning.<\/span><\/p>\n

What you will learn:<\/span><\/h3>\n