Classification of Movie Reviews with Tensorflow

In this course, you will learn to classify movie reviews as either positive or negative with the help of Tensorflow.

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Classification of Movie Reviews with Tensorflow

Task List


We will cover the following tasks in 52 minutes:


Introduction

  • A look at what we will achieve by the end of the course.
  • A look at the development environment.

Introduction

Importing Tensorflow and Dataset

  • Importing Tensorflow and Keras.
  • Importing the IMDB dataset.
  • Splitting data in training and test sets.
  • A look at training examples.

Importing Tensorflow and Dataset

Preparing the Data

  • Two approaches to making all examples uniform.
  • Padding the data to have uniform shape for all examples.

Preparing the Data

Building the Model

  • Creating a Sequential model.
  • Adding layers to our neural network model.
  • Compiling the model.
  • Looking at the model summary.
  • Splitting training set into a partial training set and a validation set.

Building the Model

Training the Model

  • Training by fitting the training data to the model.
  • Validating the training with the validation set.
  • Model evaluation on the test set.

Training the Model

Accuracy and Loss Plots

  • Using pyplot to plot loss on training and validation sets.
  • Plotting training accuracy and validation accuracy values from during training.
  • Interpreting the plots.

Accuracy and Loss Plots

Watch Preview

Note: The actual session is completely hands-on where you interact with the software while watching the host's (Amit) instructions. You can preview the instructions here

Host: Amit


Amit

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Frequently Asked Questions


In Rhyme, all sessions are completely hands-on. You don't just passively watch someone else use the software. You use the software directly. While following the host's (Amit) instructions. Using the software is the only way to understand a software!
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