All in One Offer! | Access Unlimited Courses in any category starting at just $29. Signup today. Offer Ends in: 5 Days!

Browse Library

Deploying Machine Learning Models - A Complete Guide

Learn to Deploy Machine Learning Models. Learn about Server and Serverless Frameworks Both using Python

Instructed by Cosmic .

5 days left at this price!
Get Unlimited Courses Access $29
$29
It Includes
  • Get Full Access to the platform
  • Access to 16000+ online courses
  • High Quality Recorded Lectures
  • Learn Online from Mobile/PC/Tablet
  • Assignments & Projects
  • Online iLab Access
  • Certificate of Completion
  • Download for offline viewing
  • Free Instructor Support
  • Access valid for 1 user only
  • Cancel Anytime
  • Learn the Basics of Flask
  • Learn to Deploy Machine Learning Model using Flask
  • Learn the Basics of Steamlit
  • Learn to Deploy Machine Learning Model using Streamlit
  • Learn Serverless and AWS Lambda
  • Learn to Deploy Machine Learning Model using Serverless and Lambda
  • Learn Basics of Docker
  • Learn to Deploy Machine Learning Model using Docker Container
  • Learn To Deploy model on AWS Sagemaker

Deploying Machine Learning Models - A Complete Guide

Learn to Deploy Machine Learning Models. Learn about Server and Server less Frameworks Both using Python

 

So , YOU HAVE A MACHINE LEARNING MODEL and IT IS WORKING Well ! NOW, WHAT ?

This course will help you in Deploying your Machine Learning Models in all Possible Ways Possible. We will be use Server Based and Server Less Frameworks both.

In This Course, You will Learn :-

  • Introduction

  • Flask Basics

  • PROJECT : Deploying Breast Cancer Machine Learning Model using Flask

  • Containerizing the Breast Cancer Model using Docker

  • Streamlit Basics

  • PROJECT : Deploying Heart Disease Machine Learning Model using Streamlit

  • Containerizing the Heart Disease ML Model using Docker

  • Serverless and AWS Basics

  • AWS Lambda Basics

  • PROJECT : Deploying Diabetes Prediction Machine Learning Model using AWS Lambda

  • General Overview of AWS Sagemaker

  • XgBoost using Sagemaker - Breast Cancer Classification

  • Hosting a Custom ML Model Using Sagemaker - Credit Card Fraud Detection

  • PROJECT : Deploying  Model using Sagemaker, AWS Lambda and API Gateway - Diabetes Prediction

     

We know that you're here because you value your time and Money.By getting this course, you can be assured that the course will explain everything in detail and if there are any doubts in the course, we will answer your doubts in less than 12 hours.

All the project Files are available for you.


So, What are you waiting for? Go Click on the Buy button and let's explore this exciting journey of Deploying Machine Learning Models

I will be waiting for you inside the course...

 

Cosmic

  • Basic of Machine Learning
  • Anyone Willing to learn how to Deploy machine Learning Model
  • Beginner Machine Learning or Data Science Professional Willing to Enhance their Skills
  • Intermediate Machine Learning or Data Science Professional Willing to Enhance their Skills
  • Advance Machine Learning or Data Science Professional Willing to Enhance their Skills
View More...

Section 1 : Introduction

  • Lecture 1 :

Section 2 : Flask Basics

  • Lecture 1 :
  • Intro to Flask and Making a basic API
  • Lecture 2 :
  • Recieving Data through GET Request
  • Lecture 3 :
  • Recieving Data through POST Request
  • Lecture 4 :
  • Making a HTML Form to Send inputs and Receive the Output from API

Section 3 : PROJECT : Deploying Breast Cancer Machine Learning Model using Flask

  • Lecture 1 :
  • General Overview and Business Challenge
  • Lecture 2 :
  • Importing Data and basic Cleaning
  • Lecture 3 :
  • Data Visulization, Feature Scaling and Encoding
  • Lecture 4 :
  • Model Fitting and Getting the Feature importance
  • Lecture 5 :
  • Balancing the dataset and Feature Selection
  • Lecture 6 :
  • Deploying The Model ( Part 1 )
  • Lecture 7 :
  • Deploying The Model ( Part 2 )
  • Lecture 8 :
  • Deploying The Model ( Part 3 )
  • Lecture 9 :
  • Deploying The Model ( Part 4 )
  • Lecture 10 :
  • Conclusion

Section 4 : Containerizing the Breast Cancer Model using Docker

  • Lecture 1 :
  • General Overview of Docker
  • Lecture 2 :
  • Coding the Dockerfile
  • Lecture 3 :
  • Minor PreRequisite for Containerizing
  • Lecture 4 :
  • Building and Running the Container

Section 5 : Streamlit Basics

  • Lecture 1 :
  • Intro and installing Streamlit
  • Lecture 2 :
  • Showing Dataframe and Plotting LineChart
  • Lecture 3 :
  • Showing Maps and Toggling CheckBoxes
  • Lecture 4 :
  • Conditional Rendering using Select and MultiSelect Box
  • Lecture 5 :
  • Example : Predict House Price : Getting Basics Ready
  • Lecture 6 :
  • Example : Predict House Price : Making the UI
  • Lecture 7 :
  • Example : Predict House Price : Training the Model and Showing Prediction on UI
  • Lecture 8 :
  • Project File

Section 6 : PROJECT : Deploying Heart Disease Machine Learning Model using Streamlit

  • Lecture 1 :
  • General Overview and Business Challenge
  • Lecture 2 :
  • Data import and Basic Data Cleaning
  • Lecture 3 :
  • Visualization and EDA
  • Lecture 4 :
  • Feature Engineering
  • Lecture 5 :
  • Model Building and Evaluation
  • Lecture 6 :
  • Minor Bug Fixes
  • Lecture 7 :
  • Balancing the Dataset
  • Lecture 8 :
  • Deploying the Model ( Part 1 )
  • Lecture 9 :
  • Deploying the Model ( Part 2 )
  • Lecture 10 :
  • Deploying the Model ( Part 3 )
  • Lecture 11 :
  • Conclusion

Section 7 : Containerizing the Heart Disease ML Model using Docker

  • Lecture 1 :
  • General Overview of Docker
  • Lecture 2 :
  • Coding the Dockerfile
  • Lecture 3 :
  • Requirement.txt File and Building the Docker Image
  • Lecture 4 :
  • Running the Container

Section 8 : Serverless and AWS Basics

  • Lecture 1 :
  • What is Serverless Computing?
  • Lecture 2 :
  • Function as a Service ( FaaS)
  • Lecture 3 :
  • Advantage of Serverless Computing
  • Lecture 4 :
  • Disadvantages of Serverless Computing

Section 9 : AWS Lambda Basics

  • Lecture 1 :
  • Intro
  • Lecture 2 :
  • Getting Started with AWS and Serverless and Adding Configs
  • Lecture 3 :
  • Creating Serverless and AWS Project using Terminal
  • Lecture 4 :
  • Deploy the Project on AWS

Section 10 : PROJECT : Deploying Diabetes Prediction Machine Learning Model using AWS Lambda

  • Lecture 1 :
  • General Overview and Business Challenge
  • Lecture 2 :
  • Importing Data and basic Cleaning
  • Lecture 3 :
  • Visualization and EDA
  • Lecture 4 :
  • Feature Engineering
  • Lecture 5 :
  • Model Building
  • Lecture 6 :
  • Balancing the dataset
  • Lecture 7 :
  • Refitting the Model
  • Lecture 8 :
  • Deploying the Model ( Part 1 )
  • Lecture 9 :
  • Deploying the Model ( Part 2)
  • Lecture 10 :
  • Deploying the Model ( Part 3)
  • Lecture 11 :
  • Deploying the Model ( Part 4 )
  • Lecture 12 :
  • Deploying the Model ( Part 5)
  • Lecture 13 :
  • Deploying the Model ( Part 6)
  • Lecture 14 :
  • Conclusion

Section 11 : General Overview of SageMaker

  • Lecture 1 :
  • Intro to AWS Sagemaker
  • Lecture 2 :
  • Instance Type
  • Lecture 3 :
  • Built in Algorithm
  • Lecture 4 :
  • Frameworks Offered , AWS Ground Truth and NEO
  • Lecture 5 :
  • Different API Levels
  • Lecture 6 :
  • Making a S3 Bucket
  • Lecture 7 :
  • Spinning Jupyter Notebook in Sagemaker ( Part 1)
  • Lecture 8 :
  • Spinning Jupyter Notebook in Sagemaker ( Part 2)
  • Lecture 9 :
  • Summary

Section 12 : Implementing XgBoost using Sagemaker - Breast Cancer Classification

  • Lecture 1 :
  • General Overview and Business Problem
  • Lecture 2 :
  • Data importing and Basic Data Cleaning
  • Lecture 3 :
  • Visualization, Scaling and Encoding Data
  • Lecture 4 :
  • Model Fitting and getting the Feature Importance
  • Lecture 5 :
  • Setting up everything for AWS Sagemaker
  • Lecture 6 :
  • Saving Data in S3
  • Lecture 7 :
  • Model Building and Fitting
  • Lecture 8 :
  • End Point Creation
  • Lecture 9 :
  • Prediction ( Part 1 )
  • Lecture 10 :
  • Prediction ( Part 2 )
  • Lecture 11 :
  • Conclusion
  • Lecture 12 :
  • Balancing dataset and Feature Selection

Section 13 : Hosting Custom Model on Sagemaker - Credit Fraud Detection

  • Lecture 1 :
  • Intro and Business Challenge
  • Lecture 2 :
  • Data Import
  • Lecture 3 :
  • Feature Engineering and Model Prediction
  • Lecture 4 :
  • Under Sampling the Data
  • Lecture 5 :
  • Over Sampling the Data
  • Lecture 6 :
  • Understanding the Folder Structure AWS Accepts
  • Lecture 7 :
  • Basic Setup and Model Python File
  • Lecture 8 :
  • Basic Imports and Upload to S3
  • Lecture 9 :
  • Model Building, Fitting and End Point Creation
  • Lecture 10 :
  • Conclusion

Section 14 : PROJECT : Deploying Diabetes Prediction Model using Sagemaker

  • Lecture 1 :
  • General Overview and Business Challenge
  • Lecture 2 :
  • Importing Data
  • Lecture 3 :
  • Visualization and EDA
  • Lecture 4 :
  • Feature Engineering
  • Lecture 5 :
  • Model Building
  • Lecture 6 :
  • Balancing the dataset
  • Lecture 7 :
  • Refitting the Model
  • Lecture 8 :
  • Switching everything to AWS Notebook Instance
  • Lecture 9 :
  • Model Building and Fitting
  • Lecture 10 :
  • End Point Creation
  • Lecture 11 :
  • Making the SLS Project and Coding the YAML File
  • Lecture 12 :
  • Coding the Handler file, Deployment and Testing
  • Lecture 13 :
  • Conclusion

Section 15 : Conclusion

  • Lecture 1 :
  • Conclusion
  • How do i access the course after purchase?

    Once you purchase a course (Single course or Subscription), you will be able to access the courses instantly online by logging into your account. Use the user name & password that you created while signing up. Once logged in, you can go to the "My Courses" section to access your course.
  • Are these video based online self-learning courses?

    Yes. All of the courses comes with online video based lectures created by certified instructors. Instructors have crafted these courses with a blend of high quality interactive videos, lectures, quizzes & real world projects to give you an indepth knowledge about the topic.
  • Can i play & pause the course as per my convenience?

    Yes absolutely & thats one of the advantage of self-paced courses. You can anytime pause or resume the course & come back & forth from one lecture to another lecture, play the videos mulitple times & so on.
  • How do i contact the instructor for any doubts or questions?

    Most of these courses have general questions & answers already covered within the course lectures. However, if you need any further help from the instructor, you can use the inbuilt Chat with Instructor option to send a message to an instructor & they will reply you within 24 hours. You can ask as many questions as you want.
  • Do i need a pc to access the course or can i do it on mobile & tablet as well?

    Brilliant question? Isn't it? You can access the courses on any device like PC, Mobile, Tablet & even on a smart tv. For mobile & a tablet you can download the Learnfly android or an iOS app. If mobile app is not available in your country, you can access the course directly by visting our website, its fully mobile friendly.
  • Do i get any certification after completing the course?

    Yes. Once you succesfully complete any course on Learnfly marketplace, you get a certiifcate of course completion emailed to you within 24 hours with your name & the Learnfly badge. You can definately brag about it & share it on your social media or with friends as one of your achievement. Click here to view the sample certificate Click Here
  • For how long can i access my course after the purchase?

    If you buy a single course, that course is accessible to you for a lifetime. If you go for a premium subcription, you can access all the courses on Learnfly marketplace till your subscription is Active.
  • Whats the difference between Single Course Purchase & Go Premium option?

    With Single Course Purchase, you only get an access of one single course. Whereas, with premium monhtly or annual subscription, you can access all the existing or new courses on learnfly marketplace. You can decide what option suits you the best and accordingly you can make your purchase.
  • Is there any free trial?

    Currently, we don't have any free trial but it may be available in near future.
  • What is the refund policy?

    We would hate you to leave us. However, if you are not satisfied, you can ask for a full refund within 30 days & we will be happy to assist you further.

Cosmic .,

Hi, We are Cosmic . Professionally, We are Entrepreneurs with over six years of experience in finance, Tech, Real Estate etc. We are trained at Mobile App Development, Web Development, Artificial Intelligence, Finance etc. In my courses, you will very well understand how I combine theory and Real Life Case studies to give you the best in-Class Training in any topic I teach. I am looking forward to sharing my passion and knowledge with you! Looking forward to working together!
View More...
big-data-pipeline-applied-to-ufos

Big Data Pipeline Applied to UFOs

By : Eduardo Morelli

Lecture 6

git-and-github-version-control-the-complete-startup-guide

Git and GitHub Version Control - Th...

By : Abhilash Nelson

Lecture 15

statistics-for-data-scientists-and-data-analysts

Statistics for Data Scientists and ...

By : Phikolomzi Gugwana

Lecture 31

big-data-and-hadoop

Big Data and Hadoop

By : Saheb Singh

Lecture 26

machine-learning-from-scratch-using-python

Machine Learning from Scratch using...

By : Saheb Singh

Lecture 14

data-preparation-for-analytics-a-z-alteryx-hands-on

Data Preparation for Analytics A-Z...

By : Shokat Ali

Lecture 13

Sign up and start learning
By signing up, you agree to our Terms of Use and Privacy Policy
Reset Password Request
Enter your email address and we'll send you a link to reset your password.