Search icon CANCEL
Subscription
0
Cart icon
Close icon
You have no products in your basket yet
Save more on your purchases!
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Hands-On Machine Learning on Google Cloud Platform

You're reading from  Hands-On Machine Learning on Google Cloud Platform

Product type Book
Published in Apr 2018
Publisher Packt
ISBN-13 9781788393485
Pages 500 pages
Edition 1st Edition
Languages
Authors (3):
Giuseppe Ciaburro Giuseppe Ciaburro
Profile icon Giuseppe Ciaburro
V Kishore Ayyadevara V Kishore Ayyadevara
Profile icon V Kishore Ayyadevara
Alexis Perrier Alexis Perrier
Profile icon Alexis Perrier
View More author details

Table of Contents (18) Chapters

Preface 1. Introducing the Google Cloud Platform 2. Google Compute Engine 3. Google Cloud Storage 4. Querying Your Data with BigQuery 5. Transforming Your Data 6. Essential Machine Learning 7. Google Machine Learning APIs 8. Creating ML Applications with Firebase 9. Neural Networks with TensorFlow and Keras 10. Evaluating Results with TensorBoard 11. Optimizing the Model through Hyperparameter Tuning 12. Preventing Overfitting with Regularization 13. Beyond Feedforward Networks – CNN and RNN 14. Time Series with LSTMs 15. Reinforcement Learning 16. Generative Neural Networks 17. Chatbots

How to clean and prepare the data

A novice may think that once we complete collecting data and it is imported into Google Cloud, it is finally time to start the analysis process. Conversely, we must first proceed with the preparation of data (data wrangling).

Data wrangling is the process of the transformation and mapping of data, turning raw data into formatted data, with the intent of making it more appropriate for subsequent analysis operations.

This process can take a long time and it is very cumbersome, in some cases taking up about 80 percent of the entire data analysis process.

However, it is a fundamental prerequisite for the rest of the data analysis workflow; so it is essential to acquire the best practices in such techniques. Before submitting our data to any machine learning algorithm, we must be able to evaluate the quality and accuracy of our observations. If we...

lock icon The rest of the chapter is locked
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 $15.99/month. Cancel anytime}