Deploying Machine Learning Models - A Complete Course
Master Machine Learning Model Deployment with Python
Development,Data Science and AI ML,Artificial Intelligence
Lectures -109
Resources -1
Duration -7.5 hours
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Course Description
This comprehensive course will teach you everything you need to know to deploy machine learning models in production, including Flask, Streamlit, AWS Lambda, and SageMaker. This includes using both server and serverless frameworks in Python.
Deploying Machine Learning Models - A Complete Guide Overview
This course will help you learn how to use models that are scalable, reliable, and secure. You will also learn how to choose the right deployment framework for your needs and how to securely and reliably configure and deploy your models.
Learn to use Docker to containerize your machine-learning models and configure and deploy machine-learning models. The curriculum of this course covers a wide range of topics, including:
Model deployment fundamentals
Server-based model deployment with Flask
Serverless model deployment with AWS Lambda
Model deployment on AWS SageMaker
Containerization with Docker
Goals
What will you learn in this course:
Learn the Basics of Flask
Learn to Deploy a Machine Learning Model using Flask.
Learn the Basics of Steamlit.
Learn to Deploy a Machine Learning Model using Streamlit.
Learn Serverless and AWS Lambda.
Learn to Deploy Machine Learning Model using Serverless and Lambda.
Learn the Basics of Docker.
Learn to Deploy Machine Learning Model using Docker Container.
Learn To Deploy model on AWS Sagemaker.
Learn about Model Training and End Point Hosting on Sagemaker.
Prerequisites
What are the prerequisites for this course?
This course is designed for intermediate Python developers with basic knowledge of machine learning.
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
2 Lectures
- Introduction 03:28 03:28
- Course Files
Flask Basics
4 Lectures
PROJECT : Deploying Breast Cancer Machine Learning Model using Flask
10 Lectures
Containerizing the Breast Cancer Model using Docker
4 Lectures
Streamlit Basics
7 Lectures
PROJECT : Deploying Heart Disease Machine Learning Model using Streamlit
11 Lectures
Containerizing the Heart Disease ML Model using Docker
4 Lectures
Serverless and AWS Basics
4 Lectures
AWS Lambda Basics
4 Lectures
PROJECT : Deploying Diabetes Prediction Machine Learning Model using AWS Lambda
14 Lectures
General Overview of SageMaker
9 Lectures
Implementing XgBoost using Sagemaker - Breast Cancer Classification
12 Lectures
Hosting Custom Model on Sagemaker - Credit Fraud Detection
9 Lectures
PROJECT : Deploying Diabetes Prediction Model using Sagemaker
13 Lectures
Conclusion
1 Lectures
Instructor Details
Akshay Deep Lamba
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