Skip to content

ajvill/training-data-analyst

This branch is 2984 commits behind GoogleCloudPlatform/training-data-analyst:master.

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Oct 16, 2020
da99784 · Oct 16, 2020
Oct 1, 2020
Oct 15, 2020
Sep 4, 2018
Oct 16, 2020
Aug 6, 2019
May 19, 2020
Dec 6, 2019
Sep 30, 2020
Jul 20, 2020
Sep 14, 2018
Jun 26, 2019
Oct 5, 2018
Jan 5, 2018
Jun 2, 2020
Sep 13, 2020

Repository files navigation

training-data-analyst

Labs and demos for Google Cloud Platform courses (http://cloud.google.com/training).

Contributing to this repo

  • Small edits are welcome! Please submit a Pull-Request. See also CONTRIBUTING.md
  • For larger edits, please submit an issue, and we will create a branch for you. Then, get the code reviewed (in the branch) before submitting.

Organization of this repo

Try out the code on Google Cloud Platform

Open in Cloud Shell

Courses

Code for the following courses is included in this repo:

Google Cloud Platform Big Data and Machine Learning Fundamentals

Course

https://cloud.google.com/training/courses/data-ml-fundamentals

Code

  1. GCP Big Data & Machine Learning Fundamentals

Data Engineering on Google Cloud Platform

Course

https://cloud.google.com/training/courses/data-engineering

Code

  1. Leveraging unstructured data
  2. Serverless Data Analysis
  3. Serverless Machine Learning
  4. Resilient streaming systems

Machine Learning on Google Cloud Platform (& Advanced ML on GCP)

Courses

  1. https://www.coursera.org/learn/google-machine-learning
  2. https://www.coursera.org/specializations/advanced-machine-learning-tensorflow-gcp

Codes

  1. How Google Does ML
  2. Launching into ML
  3. Introduction to TensorFlow
  4. Feature Engineering
  5. Art and Science of ML
  6. End-to-end machine learning on Structured Data
  7. Production ML models
  8. Image Classification Models in TensorFlow
  9. Sequence Models for Time-Series and Text problems
  10. Recommendation Engines using TensorFlow

Blog posts

blogs/

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 81.6%
  • Python 12.9%
  • JavaScript 2.0%
  • HTML 1.4%
  • Java 1.2%
  • Shell 0.4%
  • Other 0.5%