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Über den Kurs

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....

Top-Bewertungen

RT

Jul 26, 2020

Good explanation about how to work with pretrained embeddings, but works too slow

RD

Jul 15, 2020

Very good project to understand the use of convolution in text data.

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1 - 10 von 10 Bewertungen für Convolutions for Text Classification with Keras

von Ruslan T

Jul 26, 2020

Good explanation about how to work with pretrained embeddings, but works too slow

von RUDRA P D

Jul 15, 2020

Very good project to understand the use of convolution in text data.

von Gangone R

Jul 03, 2020

very useful course

von Md. R Q S

Sep 17, 2020

great

von tale p

Jun 28, 2020

good

von Md. R A

Jun 27, 2020

good

von Ashwin P

Jun 27, 2020

good

von p s

Jun 26, 2020

Good

von Simon S R

Sep 04, 2020

Could still be improved.

von Hanqing L

Jul 13, 2020

Insufficient insight given as why this particular setup (embedding, convolution etc.) works for classification. Resource sharing is missing: there is no code/data sharing despite of the promise in the video. Disappointing content.