Google Cloud Platform 的 Quickstarts 蠻有參考價值。
https://cloud.google.com/getting-started/#ten-min-tutorial-section
Step1: Create a VM instance running Debian 8 OS
Step2: Install Apache(2) server and put /var/www/html/index.html
Step3: Try compute engine, 其實就是 step 1 + use python for a simple http server.
Step4: Try to run github sample code. I pick the Python Flask Skeleton for Google App Engine
(a) pip use apt-get (Debian) or yum (centos or redhat)
> sudo apt-get install python-pip
(b) install google cloud SDK 包含 gcloud, gsutil, bq, etc. command-line tools.
How? 可以參考 https://cloud.google.com/sdk/downloads
Download sdk.
Run install.sh
Initialize SDK: > sudo gcloud init
不過應該有更容易的方法 install Cloud SDK, to be checked.
(c) install App Engine Python SDK: How : > sudo gcloud components install app-engine-python
(d) > sudo gcloud components install app-engine-python-extras
接下來就是參考 git 的 tutorial
https://github.com/GoogleCloudPlatform/appengine-flask-skeleton
> sudo apt-get install git
> sudo git clone https://github.com/GoogleCloudPlatform/appengine-flask-skeleton.git
> cd appengine-flask-skeleton
> sudo pip install -r requirements.txt -t lib
不過 python 仍然有問題。這是 python 最麻煩的地方。要解決 packages 之間的相容性問題。一般需要 pip, virtualenv, etc. 請參考前文用 anaconda 解決 pip, virtualenv, 和相容性問題。
我找到一個很好的 blog.
Finally I made one work in “google Interactive Tutorial” 中的 “my-instance” VM.
I install anaconda2 and anaconda3, and tensor flow on anaconda3.
Excellent explanation! Simple, clear, and beginner-friendly. For anyone looking to learn more, check out google-cloud-platform-Tutorial.
回覆刪除隨著 machine learning and deep learning 變成主流應用。Matlab 終於找到新的舞台。除了提供相關的 toolbox, app, xxxLearner (e.g. ClassificationLearner), visualization tools 之外。也更新了 data structure and load function. 本文討論 Matlab advanced data structure.
回覆刪除glock 40
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