Google Cloud Platform for Machine Learning

 

之前在 linux (including using Raspberry pi) 作了一些 Machine Learning (ML) 的試驗。用了 OpenCV, Caffe. 

自從 Google promote TensorFlow 之後。一直想再試一試。之前都是想用電競的主機或 notebook.  考慮價格高同時設定比較麻煩。因此開始留意幾家 cloud service providers. 

包含 Google (Google Cloud Platform - GCP), Amazon (AWS), Ali (阿里雲), Microsoft (Azure).

最後選用 GCP 主要是 (1) TensorFlow 就是 Google 提供，相容性應該最好。 (2) 有 300 hour free trial.

 

I checked on the web, following the following link on Udacity example

 

Step 1. 

Register in Google Cloud Platform -- easy if you have google account already.  

Create a project : My First Project (default)

 

Step 2: Click on the "Activate Google Cloud Shell" on the top right button.

 

Step 3: in the shell window

List machine types:

> gcloud compute machine-types list

 

Step 4: Create an instance (VM?)

> gcloud compute instances create tf  --image container-vm  --zone asia-east1-c  --machine-type n1-standard-2

=> tf is the name of the VM?  (image container)  The container-vm is deprecate.  

=> asia-east1 can change to europe or us-west or us-east

=> n1 type computer and 2 CPUs

 

Step 5:  copy a tensor flow example from Udacity

sudo docker run -d -p 8888:8888 --name tf b.gcr.io/tensorflow-udacity/assignments:0.5.0

 

 

Step 6: Find the instance in the dashboard and edit default network

 

 

Too hard to get it works.

 

Finally I made one work in “google Interactive Tutorial” 中的 “my-instance” VM.

I install anaconda2 and anaconda3, and tensor flow on anaconda3. 

 

 

Back to wordpress first.   參考梅問題教學網

以下是 wordpress 的 ip address and paswd.

 

 

Finally I found the "Getting Started with Google Cloud Platform"