Classroom course

Deployment of Machine Learning models: FastAPI


classroom course

Deployment of Machine Learning models: FastAPI


REQUEST INFORMATION
Price
787 € + VAT

Duration
8 hours

Date:
July 27th | October 26th

Qualification obtained
Certificate

Course code
AGSAI004

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Machine Learning model building aims to develop concrete solutions. To make this happen, the models must be deployed in a production environment, so that users can actively use them, exploit their predictions, and request processing.

Who is it for?

The course is aimed at:

  • programmers
  • graduate students who know programming
Objective

This course covers the fundamental steps of the deployment process, which begins at the end of the design of the machine learning model. Through the deployment, the predictive capabilities of the model will be made available to the ecosystem of business applications.

Program
Machine Learning Model Deploy
  • 1. Modern web applications: notes on microservices architecture
  • 2. FastAPI
    • 2.1 FastAPI introduction
    • 2.2 FastAPI installation
    • 2.3 Writing your first API in FastAPI
    • 2.4 Example of deploying a Machine Learning model with FastAPI
    • 2.5 Insights and references
  • 3. Containerization
    • 3.1 Pack Docker image for application
    • 3.2 Launch container and query service
    • 3.3 The importance of logging
    • 3.2 Docker registry: archive and retrieve the image
Classroom and safety rules
To comply with Covid safety regulations, the classroom will be equipped with special filtering systems special air filtering systems and participation will be limited to a maximum of 8 participants with a green pass. The course will be confirmed upon reaching the minimum number of 4 participants.

Machine Learning model building aims to develop concrete solutions. To make this happen, the models must be deployed in a production environment, so that users can actively use them, exploit their predictions, and request processing.

Who is it for?

The course is aimed at:

  • programmers
  • graduate students who know programming
Objective

This course covers the fundamental steps of the deployment process, which begins at the end of the design of the machine learning model. Through the deployment, the predictive capabilities of the model will be made available to the ecosystem of business applications.

Program
Machine Learning Model Deploy
  • 1. Modern web applications: notes on microservices architecture
  • 2. FastAPI
    • 2.1 FastAPI introduction
    • 2.2 FastAPI installation
    • 2.3 Writing your first API in FastAPI
    • 2.4 Example of deploying a Machine Learning model with FastAPI
    • 2.5 Insights and references
  • 3. Containerization
    • 3.1 Pack Docker image for application
    • 3.2 Launch container and query service
    • 3.3 The importance of logging
    • 3.2 Docker registry: archive and retrieve the image
Classroom and safety rules
To comply with Covid safety regulations, the classroom will be equipped with special filtering systems special air filtering systems and participation will be limited to a maximum of 8 participants with a green pass. The course will be confirmed upon reaching the minimum number of 4 participants.
REQUEST INFORMATION
Price
787 € + VAT

Duration
8 hours

Date:
July 27th | October 26th

Qualification obtained
Certificate

Course code
AGSAI004

subscribe