Giter VIP home page Giter VIP logo

gccd-heartfelt's Introduction

gccd-heartfelt

This repository hosts the code used at the demo for Google Cloud's Professional Machine Learning Engineer examination session at Google Cloud Community Days - India (Jan 22-23, 2021).

Note: I welcome you to show me the improvements you make to my model/dataset! You can also show me any cool applications you build with my code as a starting point. Please open a Github Issue and upload your files. I will be happy to leave my comments. But please don't ask me to fix bugs!

Getting Started

Please download the dataset file titled heartfelt_dataset.csv (don't rename it) as well as the Jupyter notebook corresponding to your environment. Use Heartfelt (GCP) when running on Google Cloud's AI Platform and Heartfelt (Colab) otherwise. You can run each cell one at a time and play around with the code.

If you're feeling up to it, there are homework exercises at the end you can do. I would love to see what you make!

Setting up on Colab

Open Colab and upload the notebook. Without changing the name, upload the dataset to the /content folder (it will be opened by default when you click the Files tab at the left of the screen). You can run the cells one by one and play around with the code. Colab is 100% free.

Setting up on GCP

Set up your GCP account as required; you may need to use your credit card to avail of the free $300 trial. Go to the Notebooks section under AI Platform (not Unified AI Platform). Click New Instance and select TensorFlow 2.3 Enterprise > Without GPUs. You can change the instance name (or leave it as it is) and click Create. It will take about 10 minutes before the Open Jupyter Lab option becomes available. When it does, click the button, and Jupyter Lab will open in a new tab.

You can use the Files pane at the left of the screen to upload the Jupyter notebook and dataset file (without changing the name). Double click the notebook to open it. You can run the cells one by one and play around with the code. You may need to go to the Jobs and Models sections of the AI Platform to enable these APIs.

Be sure to delete your instance when you're done. Otherwise, you will burn right through your $300 credit! There are still some minor costs associated with your instance when it is turned off, so to be entirely sure that you aren't losing money, please delete your instance. You will also need to delete the model you deploy to AI Platform Models after you finish playing with it.

gccd-heartfelt's People

Contributors

virenlr avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.