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Hands-On Machine Learning on Google Cloud Platform

You're reading from   Hands-On Machine Learning on Google Cloud Platform Implementing smart and efficient analytics using Cloud ML Engine

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788393485
Length 500 pages
Edition 1st Edition
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Authors (3):
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Alexis Perrier Alexis Perrier
Author Profile Icon Alexis Perrier
Alexis Perrier
V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Table of Contents (18) Chapters Close

Preface 1. Introducing the Google Cloud Platform FREE CHAPTER 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

Setting up a data science stack on the VM

So, now we have a VM running and we're able to send files to it, connect to it, and modify it. Everything is ready for us to set it up for data science!

We will install the Python Miniconda stack from continuum, much smaller than the full Conda distribution. Do SSH into your instance.

  1. Install the mini sudo apt-get update sudo apt-get install bzip2 wget from https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh using the following command:
bash Miniconda2-latest-Linux-x86_64.sh
  1. And then install the Python stack with conda:
$ conda install scikit-learn pandas jupyter ipython

Don't forget to do this:

$ source .bashrc
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