Build & Host AI Apps (Python) + 6 Real World Projects
Python Streamlit Apps: EDA | NLP | cancer Prediction | Forecasting | Customer Lifetime Value | Market Basket Analysis
What you’ll learn
- How to build AI applications
- How to use streamlit
- Learn how to apply the concepts of AI in a real-world web application
- How to host an AI web application
- None. Concepts and Python are covered extensively to assist those who are new to Python & AI.
The AI landscape is evolving fast, though these are still early days for AI. The focus of AI has been more on building models and analyzing data, while users were asking for crisp outputs and self-use interactive applications.
In summary, end-users wanted a simple web app to view the results of AI algorithms and data scientists wanted a platform to build AI web apps easily & faster. Streamlit addressed both these needs perfectly.
I am going to demonstrate how to build a healthcare AI app (and few other examples) in less than 50 lines of code using streamlit platform. This covers AI/ML code as well as code for the app including the user interface. We will start with the functionalities of streamlit and then cover how to build and host web applications.
For those who are new to AI, Machine Learning, Deep Learning, Natural Language Processing (NLP), and Exploratory Data Analysis (EDA) are included in the program. Python is also covered extensively to assist those who are looking for a refresher on python topics or are new to python itself.
In all, this program can be pursued by both experienced professionals as well as those who are new to the world of AI.
Let’s build stunning web-based AI apps!
Who this course is for:
- Experienced data scientists
- College students
- Data scientists who are starting their career
- Web application developers
- IT professionals who want to switch their careers to AI.