Advanced Machine Learning on Google Cloud Specialization

What you will learn from this course

  • large dataset using Datalab and BigQuery
  • How to use Pandas in Datalab and sample a dataset for local development
  • Develop a machine learning model in Tensorflow
  • How to preprocess data at scale for machine learning
  • How to use Qwiklabs to complete each of your labs using Google Cloud Platform
  • How to bring your data to the cloud
  • How to recognize the ways that our model is dependent on our data, make cost-conscious engineering decisions
  • How to identify performance considerations for machine learning models
  • Understand the tools and systems available
  • Learn about the rapid growth in high-resolution image data available and the types of applications
  • What is Data Scarcity and why data scarcity is important
  • What is sequence
  • How our traditional optimization procedure applies to RNNs
  • LSTMs, Deep RNNs, working with real world data, and more
  • Different ways of working with text and how to create your own text classification models
  • How to build a recommendation system using characteristics of the users and items
  • How the data of the interactions between users and items from many different users can be combined to improve the quality of predictions
  • How various recommendation systems can be combined as part of a hybrid approach
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