Auto Learning On Google Cloud Specialization

Use Vertex AI AutoML together with BigQuery ML to construct, train, as well as deploy ML models

Implement auto learning models using Keras as well as TensorFlow ii.x

Implement motorcar learning inward the corporation best practices

Describe how to perform exploratory data analysis in addition to amend data lineament

What is motorcar learning, too what kinds of problems tin it solve? How can you lot build, develop, together with deploy automobile learning models at scale without writing a single business of code?  When should you purpose automated automobile learning or custom training?  

This class teaches you how to build Vertex AI AutoML models without writing a unmarried line of work of code; make BigQuery ML models knowing basic SQL; make Vertex AI custom training jobs you lot deploy using containers (alongside trivial knowledge of Docker); function Feature Store for data direction and governance; function feature technology for model improvement; decide the appropriate information preprocessing options for your function case; role Vertex Vizier hyperparameter tuning to contain the right mix of parameters that yields accurate, generalized models together with cognition of the theory to solve specific types of ML problems, write distributed ML models that scale in TensorFlow; together with leverage best practices to implement automobile learning on Google Cloud.

> By enrolling in this specialization yous hold to the Qwiklabs Terms of Service as gear up out in the FAQ as well as located at: 

This specialization incorporates hands-on labs using our Qwiklabs platform.

These hands on components will allow you lot employ the skills yous learn inwards the video lectures. Projects volition incorporate topics such equally Google Cloud Platform products, which are used together with configured within Qwiklabs. You can expect to hit practical hands-on feel amongst the concepts explained throughout the modules.