Course Description

Building Machine Learning Web Apps

Artificial Intelligence and Machine Learning is affecting every area of our lives and society. Google, Amazon, Netflix, Uber, Facebook and many more industries are using AI and ML models in their products. 

What if you could also build your own machine learning models?

What if you can build something useful from the ML model you have spend time creating and make some profit whiles helping people and changing the world?

In this wonderful course, we will be exploring the various ways of converting your machine learning models into useful web applications and products.

We will learn

  • how to setup your Data Science and ML workspace locally
  •  how to build machine learning models
  • how to interpret them  
  • how to build ML web apps using the models we have created.
  • how to build packages from your ML Models
  • how to deploy your products
  • etc

Join us as we explore the world of building ML Web Apps and Products in python.

See you in the Course,Stay blessed.

This is an ongoing course which will be periodically updated


Jesse E. Agbe

Jesse has been a student of the bible since he got his first bible.He is an avid reader on optimization,productivity,technology.He is a student of ideas,beliefs and philosophies with a desire to see improvement and development in the lives of everyone.His driving goal is to help people to optimize standard technologies in solving certain problems as well as to grow their faith.Jesse loves questions and he is passionate about why things are the way they are and how to be efficient.He is a student,an author and a simple programmer.

Course curriculum

  • 1

    Module 01 - Intro to Building ML Models

  • 2

    Module 02 - Crash Courses on Tools

    • Flask Crash Course - Installation and Basic App

    • Flask Crash Course - Rendering HTML

    • Flask Crash Course -Working with Jinja(Sending Data From Back-End to Front-End)

    • Flask Crash Course - Receiving Input From Front End to BackEnd

    • Flask Crash Course - Processing Data At Backend

    • Flask Crash Course - Working with Databases using SQLAlchemy

    • Flask Crash Course - Retrieving Data From Database

    • Flask Crash Course - Searching Database

    • Streamlit Crash Course 1

    • Streamlit Crash Course 2 - Work Arounds and Plots

    • FastAPI Tutorial - Basics

    • Hug Framework Tutorial

    • Building A Simple Blog App with Streamlit and Python

    • Adding a Simple Login & Sign Up Section to Streamlit App

    • Updating our Streamlit Blog with Login and Sign Up

    • Securing the Login Section Against SQL Injection

  • 3

    Module 03 - Building ML Web Apps

    • Introduction

    • CMC Predictor ML App with Streamlit - Demo

    • Setting Up Our Workspace For the CMC- Predictor App

    • Building the EDA Section of CMC Predictor ML App

    • Building the Prediction Section of CMC_ Predictor ML App

    • Building ML Flask Apps-News Classifier-App -Demo

    • Building ML Flask App-News Classifier- Setting Up and Basic App

    • Building ML Flask Apps - News Classifier - Embedding Our ML Models

    • Building ML Flask App - News Classifier - Beautifying The Front-End

    • Salary Predictor ML App with Streamlit -Demo

    • Setting Up Our Workspace ,Installation and App Structure

    • Building The Exploratory Data Analysis Section(EDA) of Our Salary Predictor ML App

    • Building The EDA Section of Salary Predictor ML App [Part 2]

    • Building The Prediction Section Of Our Salary Predictor ML App

    • Building NLP Apps - Sentiment Analysis App with Streamlit

    • Building NLP Apps - Summarizer and Entity Checker App with Streamlit and SpaCy

    • Building NLP Apps -Document Redactor App with SpaCy and Streamlit

    • Predicting Customer Churn ML App with Streamlit -Demo

    • Building Customer Churn Prediction ML App

    • Building A Drag & Drop Semi-Automated ML App

    • Password Strength Classifier ML App

    • Car Evaluation ML App with Streamlit

    • Face Detection App-Demo

    • Building Computer Vision ML App - Face Detection App

    • Face Detection App - Files and Code

    • Emoji Lookup App -Demo

    • Simple Streamlit App with Login and Sign-Up Section

    • Search Term Trend App For Programming Languages

    • Building a Programming Languages Trends App with Streamlit using the Layout

    • Your Opinion About the Course So Far

  • 4

    Module 04 - Deploying ML Web Apps

    • How To Deploy Streamlit Apps to Heroku

    • Updating An Already Deployed Streamlit App on Heroku

    • How To Deploy Streamlit on AWS Ec2

    • How To Deploy Streamlit Apps with Docker

    • How To Deploy Streamlit Apps to GCP App Engine

    • Deploying with Docker and GCP Documents

    • Updating and Deleting A Deployed Streamlit App on GCP

    • How to Deploy Streamlit OpenCV Face Detection on Heroku

  • 5

    Module 05 - Miscellaneous, Monitoring Web Apps etc

    • Course Materials and Resources

  • 6

    Module 06 - Using ML Models as Packages

    • Using ML Models as Packages-NewsClassifier-Demo

    • NewsClassifier ML Package - Designing the Package

    • NewsClassifier ML Package - Loading The ML Models

    • NewsClassifier ML Package- Classifying News

    • NewsClassifier ML Package - Unit Testing Our Package

    • NewsClassifier ML Package - Building Our Package with Setuptools

    • NewsClassifier ML Package - Publishing to TestPyPI and PyPI

    • NewsClassifier ML Package - Building with Poetry

    • Using ML Models as Packages - GenderClassifier-Demo

    • GenderClassifier ML Package - Creating Package and the Class Object

    • GenderClassifier ML Package - Adding the Prediction Function

    • GenderClassifier ML Package - Loading Different Models

    • GenderClassifier ML Package - Classifying Names

    • GenderClassifier ML Package - Unit Testing Our Package

    • GenderClassifier ML Package - Building the Package with Setuptools

    • GenderClassifier ML Package - Building Our Package with Poetry

    • GenderClassifier ML Package - Publish the Package to PyPI with Poetry

    • SpamDetector ML Package -Indepth with Poetry

  • 7

    Module 07 - Serving ML Models as API

    • FastAPI Tutorial-Serving ML Models As API

    • FastAPI Tutorial-Adding Validations

    • FastAPI Tutorial - How to Build A Web /REST API

    • Hug Framework Crash Course

    • Hug Framework - Building 3 ML Products At Once with Hug

  • 8

    Module 09- Data Science Project

    • Data Science Project From Scratch - Predicting Hepatitis Mortality with ML

    • Building ML Web App with Streamlit - Hepatitis Predictor ML App

    • Building ML Web App with Flask - Hepatitis Predictor ML App