LinkedIn – Deep Learning with Python and Keras: Build a Model For Sentiment Analysis 2024-2
LinkedIn – Deep Learning with Python and Keras: Build a Model For Sentiment Analysis 2024-2
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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.
What you will learn:
- Introduction to sentiment analysis: An overview of sentiment analysis and its applications.
- Text preprocessing for sentiment analysis: How to clean, normalize, and transform text into a format that can be used by deep learning models.
- Building Deep Learning Models for Sentiment Analysis: How to build and train DNN, RNN, and LSTM models using Python and Keras.
- Evaluating Deep Learning Models: How to evaluate the performance of deep learning models for sentiment analysis.
- Working with Google Colab: How to use Google Colab to run Python code and train deep learning models.
- Text visualization with word clouds: How to visualize text using word clouds to better understand data.
Who is this course suitable for?
- Python developers: who want to use deep learning to solve sentiment analysis problems.
- Data science students: who want to learn about deep learning and its applications in sentiment analysis.
- Data engineers: who want to implement deep learning models for sentiment analysis in their projects.
- Anyone: who is interested in deep learning and sentiment analysis.
Course Details: Deep Learning with Python and Keras: Build a Model for Sentiment Analysis
- Publisher: LinkedIn
- Instructor: Janani Ravi
- Training level: Advanced
- Training duration: 1 hour and 55 minutes
Course headings
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Sample course video
Installation Guide
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Subtitles: English
Quality: 720p
Download link
File(s) password: www.downloadly.ir
File size
177 MB
