TensorFlow (Beginner): Basic Image Classification

In this course, you will learn how to perform image classification with Tensorflow. You will train a neural network model to classify images of clothes from the popular Fashion MNIST dataset.

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TensorFlow (Beginner): Basic Image Classification

Duration (mins)

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Task List


We will cover the following tasks in 58 minutes:


Introduction

  • A look at what we will create.
  • A look at the development environment.

Introduction

Data Preprocessing

  • Feature scaling.
  • Plotting images from the dataset.

Data Preprocessing

Making Predictions

  • Making predictions on the test data.
  • Plotting predictions in the Notebook.
  • Making prediction on a single image input.

Making Predictions

Importing Tensorflow and the Dataset

  • Importing Tensorflow and Keras.
  • Importing the Fashion MNIST dataset.
  • Splitting data in training and test sets.
  • A look at shape of the data.

Importing Tensorflow and the Dataset

Building the Model

  • Creating a Sequential model.
  • Adding layers to our neural network model.
  • Compiling the model.

Building the Model

Training the Model

  • Training by fitting the training data to the model.
  • Model evaluation on the test set.
  • Understanding overfitting.

Training 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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