TensorFlow (Beginner): Classification of Movie Reviews

In this course, you will learn to classify movie reviews as either positive or negative with the help of Tensorflow and Keras. We will use the popular IMDB dataset in this course.

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TensorFlow (Beginner): Classification of Movie Reviews

Duration (mins)

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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

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

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

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

Amit

About the Host


I have been writing code since 1993, when I was 11, and one of the first things I remember I wrote was a database management software for a local hospital. More recently, I wrote an award winning Chatbot for a multi-billion-revenue company! In the last one year, I've been learning Machine Learning, NLP and Deep Learning and I'm very excited to share my learnings with you with the help of Rhyme.com !



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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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