Train deep neural network free using google colaboratory.
GPU and TPU compute for free? Are you kidding?
Google Colaboratory is a free Jupyter notebook environment that requires no setup and runs entirely in the cloud.
With Colaboratory you can write and execute code, save and share your analyses, and access powerful computing resources, all for free from your browser. If you don’t have money to procure GPU and want to train neural network or want to makes hands dirty with zero investment then this if for you. Colab is a Google internal research tool for data science.
You can use GPU as a backend for free for 12 hours at a time.
It supports Python 2.7 and 3.6, but not R or Scala yet.
Many people want to train some machine learning model or deep learning model but playing with this requires GPU computation and huge resources that blocking many people to try out these things and make hands dirty.
Google Colab is nothing but cloud-hosted jupyter notebook.
Colaboratory is a free Jupyter notebook environment provided by Google where you can use free GPUs and TPUs which can solve all these issues. The best thing about colab is TPUs (tensor processing unity) the special hardware designed by google to process tensor.
To start with this you should know jupyter notebook and should have a google account.
Click on the above link to access google colaboratory. This is not only a static page but an interactive environment that lets you write and execute code in Python and other languages. You can create a new Jupyter notebook by File →New python3 notebook. clicking New Python3 Notebook or New Python2 Notebook.
We will create one python3 notebook and it will create one for us save it on google drive.
Colab is an ideal way to start everything from improving your Python coding skills to working with deep learning frameworks, like PyTorch, Keras, and TensorFlow and you can install any Python package which is require for your python coding like from simple sklearn, numpy too TensorFlow.
You can create notebooks in Colab, upload existing notebooks, store notebooks, share notebooks with anyone, mount your Google Drive and use whatever you’ve got stored in there, import most of your directories, upload notebooks directly from GitHub, upload Kaggle files, download your notebooks, and do whatever your doing with your local jupyter notebook.
On the top right you can choose to connect to hosted runtime or connect to local runtime.
Set up GPU or TPU:-
It’s very simple and straight forward as going to the “runtime” dropdown menu, selecting “change runtime type” and selecting GPU/TPU in the hardware accelerator drop-down menu!
Now you can start coding and start executing your code !!
How to install a framework or libraries?
It’s as simple as writing import statement in python!.
!pip install fastai
use normal pip install command to install different packages like TensorFlow or PyTorch and start playing with it.
For more details and information