From ML model to production code
best practices to deploy and monitor your app on AWS
2021, April 9
start: 12 am UTC
Duration: 4 hours 15 minutes online
FOR WHOM?
Juniors - Beginners with a basic grasp on ML models that wish to learn best practices on how to deploy their scalable models on the Cloud using AWS free tier. We will start with a pre-trained model, plan and build the API using FastAPI, makeing it resilient and scalable. Deploy it on cloud and watch it evolve from monoliyth micro-services.
Bojan Miletic
CEO at Softerrific
Bojan Miletic CEO at Softerrific Bojan has been working with Python for almost a decade. He has been CEO in several startups which allowed him to work in many different roles (usually at the same time). This provided him with a valuable perspectives and allow to observer problems from developer and business perspective at the same time. Also he loves making cookies.
https://www.linkedin.com/in/boyan-miletic/
WORKSHOP FORMAT
The best way to improve your professional skills
Introduction

30 min
Training 

2.5 hours
Breaks 

30 minutes
QA

20 min
WORKSHOP PROGRAM
2021, April 9
12:00 – 12:30
Welcome speech. Introduction.
12:30 – 12:40
Intro to AWS
12:40 – 13:10
Create the model (1st iteration)
Install dependecies / setup virtual env
Describe the chosen model
Create the API for the model using FastAPI 101
Now we run ML with API calls
13:10 – 13:20
Break
13:20 – 14:00
Deploy the model (2nd architecture)
Docker 101
Overview of monolithic architecture
Deploy like production
14:00 - 14:30
Microservices
101 (separation of concerns)
Scale your model using microservices
14:30 - 14:50
Break
14:50 - 15:20
Monitoring
Why is it necessary
Set up health checks
15:20 - 15:50
Conclusion
15:50 -16:15
Q&A
WHAT YOU NEED BEFORE WE START:
1
New AWS account (free tier)
2
Install Docker Desktop or Docker Engine
3
Mug of Coffee or Tea
4
Smiley face :)
WHAT YOU LEARN
For this workshop, you will receive a pre-built machine learning model. We will then build and test a REST API for the model using the amazing FastAPI framework. You will deploy the model in a real Cloud environment similar to production. We will look into making the app scalable, applying common sense through the whole process and iterating through the details. We will then introduce the concept of microservices and instruct you on how to migrate the entire monolithic system into a microservices architecture. This will demonstrate how to improve the architecture of your application and when is the most suitable time to do so. Into the bargain, we are going to set up monitoring and see how we can scale the system up and down using the incredible magic of AWS Cloud systems. And with the help of little elves in the bytes forest, we are hopefully going to do it within the free tier, and not getting supercharged. :crossed_fingers: Best part? You will get the chance to ask as many questions as you wish throughout the entire process!
    COURSE BENEFITS:
    You will be able to upgrade your AWS skills, a widely required skill nowadays.
    You will be able to use best practices for spotting AWS hidden costs and save money on the Cloud for the rest of your life.
    You will learn how to deploy a Machine Learning model into production with REST APIs using Python.
    You will be able to plan and write REST APIs using the framework of the moment, FastAPI.
    You will be able to setup monitoring features on AWS CloudWatch, that will make your application safer and more reliable.
    You will learn about microservice architecture and the best way to turn a monolithic application into a microservices.
    WORKSHOP
    Smart Bird
    $199
    2021, April 9
    Time 12AM UTC
    4 HOURS 15 MINUTES LONG
    Book Now 50 participants ONLY
    Geekle Corp.
    910 Foulk Road, Suite 201
    Wilmington, DE
    19803, USA
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