Building Machine Learning Web Apps with Python
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- Building Machine Learning Models with Python
- Build Machine Learning Web Apps
- How to Convert ML Models into Simple and Useful Products
- How to Use ML Models as Packages
- Embedding ML Models into Web Apps [Flask,Streamlit,etc]
- How to use Streamlit to build ML apps
- How to use Flask to build web applications
- Productionize ML Models
- Understand the basics of python and machine learning
- Basic Knowledge of HTML,CSS
- Ability to work around a computer and a terminal
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.
The opportunities and advantages of Machine Learning is quite numerous.
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 move beyond just building machine learning models into build products from our ML Models.
Products that you can give to your customers and other users to benefit from. We will be adding simple UI to our AI and ML models.
With every section of the course you will develop new skills and improve your understanding of this challenging yet important sub-field of Data Science and Machine Learning.
This course is unscripted,fun and exciting but at the same time we dive deep into building Machine Learning web applications.
What You will Gain in this Course
In this course you will develop new skills as you learn:
how to setup your Data Science and ML work-space locally.
how to build machine learning models.
how to interpret ML models with Eli5.
how to serialize and save ML models.
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.
Join us as we explore the world of building Machine Learning apps and tools.
- Programmers and Developers
- Any one interested in building web apps
- ML Engineers and Data Scientist
- Beginner Python Developers interested in Machine Learning and Data Science
- People curious about how to build and productionize their machine learning models
Ways To Productionize Your Machine Learning Models
Using Web Apps (Flask,Pyramid,Django,Express,etc)
Using Your ML Models as API
Using Your ML Models as a Package
So far we have seen how to productionize our ML models in several ways. Another great tool you can use to simplify the building of these ML products is to use Hug.
Hug is a framework that exposes your code in several ways specifically in 3 Main Ways
In this section we will learn how to do so.