Apply Word Embeddings for Text Classification
Use 1D Convolutions as Feature Extractors for Text in NLP
Perform Binary Text Classification using Deep Learning with Keras
Welcome to this hands-on, guided introduction to Text Classification using 1D Convolutions with Keras. By the end of this project, you will be able to apply word embeddings for text classification, use 1D convolutions as feature extractors in natural language processing (NLP), and perform binary text classification using deep learning. As a case study, we will work on classifying a large number of Wikipedia comments as being either toxic or not (i.e. comments that are rude, disrespectful, or otherwise likely to make someone leave a discussion). This issue is especially important, given the conversations the global community and tech companies are having on content moderation, online harassment, and inclusivity. The data set we will use comes from the Toxic Comment Classification Challenge on Kaggle. To complete this guided project, we recommend that you have prior experience in Python programming, deep learning theory, and have used either Tensorflow or Keras to build deep learning models. We assume you have this foundational knowledge and want to learn how to use convolutions in NLP tasks such as classification. Note: This course works best for learners based in the North America region. We’re currently working on providing the same experience in other regions.
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction and Import Packages
Load and Explore the Data
Data Preparation — Tokenize and Pad Text Data
Prepare Embedding Matrix with Pre-trained GloVe Embeddings
Create the Embedding Layer
Build the Model
Train the Model
Model Evaluation - Classify Toxic Comments
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
Good explanation about how to work with pretrained embeddings, but works too slow
Very good project to understand the use of convolution in text data.
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Can I complete this Guided Project right through my web browser, instead of installing special software?
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