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Build a Deep CNN Image Classifier with Any Images

Nicholas Renotte via YouTube

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Overview

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This tutorial walks through an end-to-end binary image classification pipeline in Python, including collecting and preprocessing images, building and training a deep neural network with Keras and TensorFlow, evaluating predictions, and saving the model.

Syllabus

- Start
- Explainer
- PART 1: Building a Data Pipeline
- Installing Dependencies
- Getting Data from Google Images
- Load Data using Keras Utils
- PART 2: Preprocessing Data
- Scaling Images
- Partitioning the Dataset
- PART 3: Building the Deep Neural Network
- Build the Network
- Training the DNN
- Plotting Model Performance
- PART 4: Evaluating Perofmrnace
- Evaluating on the Test Partition
- Testing on New Data
- PART 5: Saving the Model
- Saving the model as h5 file
- Wrap Up

Taught by

Nicholas Renotte

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