Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Intelligent Projects Using Python

You're reading from   Intelligent Projects Using Python 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras

Arrow left icon
Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788996921
Length 342 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Santanu Pattanayak Santanu Pattanayak
Author Profile Icon Santanu Pattanayak
Santanu Pattanayak
Arrow right icon
View More author details
Toc

Table of Contents (12) Chapters Close

Preface 1. Foundations of Artificial Intelligence Based Systems 2. Transfer Learning FREE CHAPTER 3. Neural Machine Translation 4. Style Transfer in Fashion Industry using GANs 5. Video Captioning Application 6. The Intelligent Recommender System 7. Mobile App for Movie Review Sentiment Analysis 8. Conversational AI Chatbots for Customer Service 9. Autonomous Self-Driving Car Through Reinforcement Learning 10. CAPTCHA from a Deep-Learning Perspective 11. Other Books You May Enjoy

The diabetic retinopathy dataset

The dataset for the building the Diabetic Retinopathy detection application is obtained from Kaggle and can be downloaded from following the link: https://www.kaggle.com/c/ classroom-diabetic-retinopathy-detection-competition/data.

Both the training and the holdout test datasets are present within the train_dataset.zip file, which is available at the preceding link.

We will use the labeled training data to build the model through cross-validation. We will evaluate the model on the holdout dataset.

Since we are dealing with class prediction, accuracy will be a useful validation metric. Accuracy is defined as follows:

Here, c is the number of correctly classified samples, and N is the total number of evaluated samples.

We will also use the quadratic weighted kappa statistics to determine the quality of the model, and to have a benchmark as to how...

You have been reading a chapter from
Intelligent Projects Using Python
Published in: Jan 2019
Publisher: Packt
ISBN-13: 9781788996921
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image