In this liveProject, you’ll explore a dataset of movie reviews and prepare it for sentiment analysis. The dataset you've provided is balanced between positive and negative reviews, but is encoded in such a way that you will need to use the dictionary (lookup) in this dataset package to decode the content to plain text. Your challenges will include decoding the data to plain text, and then converting the plain text into tokens in a Pythonic manner.
This liveProject is for Python programmers interested in common tools for encoding data for NLP. To begin this liveProject, you will need to be familiar with:
- Intermediate Python, with basics of NumPy and pandas
- Basics of Jupyter Notebook
- Basics of Google Colab notebook
- Basics of TensorFlow
- Basics of NLP
- Basics of deep learning
you will learn
In this liveProject, you’ll learn the basics of encoding and decoding techniques. These are common techniques for solving natural language processing (NLP) problems.
- Use tf.keras.datasets module for accessing IMDb movie review dataset
- Learn NumPy array indexing techniques
- Understand Python dictionary data structure, and how to edit and manipulate it
- Use a dictionary to decode and encode data
- You choose the schedule and decide how much time to invest as you build your project.
- Project roadmap
- Each project is divided into several achievable steps.
- Get Help
- While within the liveProject platform, get help from other participants.
- Compare with others
- For each step, compare your deliverable to the solutions by the author and other participants.