Deep Learning with Python and Keras: Build a Model For Sentiment Analysis

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Janani Ravi

1:55:38

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01 - Introduction

01 - An overview of sentiment analysis.mp4

04:47

02 - Prerequisites.mp4

00:54

02 - 1. Overview of Sentiment Analysis

01 - Preprocessing text for sentiment analysis.mp4

02:50

02 - Word vector encodings and word embeddings.mp4

06:11

03 - Types of sentiment analysis.mp4

03:41

04 - Approaches and challenges in sentiment analysis.mp4

05:50

03 - 2. Cleaning and Preprocessing Text Data

01 - Getting set up with Google Colab.mp4

03:45

02 - Importing Python modules and loading data.mp4

03:56

03 - Analyzing word lengths across sentiment categories.mp4

04:17

04 - Cleaning and preprocessing text.mp4

06:13

05 - Visualizing text using word clouds.mp4

01:45

04 - 3. Sentiment Analysis Using Dense Neural Networks

01 - Feed-forward neural networks.mp4

04:31

02 - Splitting data into training test and validation sets.mp4

03:46

03 - Representing text using count vectorization.mp4

07:51

04 - Configuring the dense neural network (DNN).mp4

05:15

05 - Training and evaluating the DNN.mp4

03:13

06 - Configuring the count vectorizer as a model layer.mp4

02:33

07 - Representing text using TFIDF vectorization.mp4

05:09

08 - Training and evaluating the model.mp4

03:20

09 - Representing text using integer sequences.mp4

03:08

10 - Training ADNN using embeddings.mp4

07:14

05 - 4. Sentiment Analysis Using Recurrent Neural Networks

01 - Recurrent neural networks.mp4

04:13

02 - Long memory cells.mp4

05:09

03 - The LSTM and GRU cells.mp4

03:44

04 - Training a recurrent neural network.mp4

03:41

05 - Training an LSTM network.mp4

03:09

06 - Serializing a model to disk and loading the model.mp4

03:32

06 - Conclusion

01 - Summary and next steps.mp4

02:01

Description

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.

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Python

Artificial Intelligence

Janani Ravi

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.