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Learner Reviews & Feedback for Text Classification Using Word2Vec and LSTM on Keras by Coursera Project Network

About the Course

In this 2-hour long project-based course, you will learn how to do text classification use pre-trained Word Embeddings and Long Short Term Memory (LSTM) Neural Network using the Deep Learning Framework of Keras and Tensorflow in Python. We will be using Google Colab for writing our code and training the model using the GPU runtime provided by Google on the Notebook. We will first train a Word2Vec model and use its output in the embedding layer of our Deep Learning model LSTM which will then be evaluated for its accuracy and loss on unknown data and tested on few samples. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....
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1 - 2 of 2 Reviews for Text Classification Using Word2Vec and LSTM on Keras

By Kenjabekova R D

Oct 28, 2020

Excellent

By Keyi F

Apr 30, 2021

just a feedback. for the graded quiz I have to select the wrong answers to pass :D.

great project worth the time but the whole project can be shortened if we skip the part on manually splitting the data into train, test and validation steps.