Build AI Machine Learning Apps Using Streamlit and Python paid course free. You will learn Apps for EDA | NLP | cancer Prediction | Sales Forecasting | CLV (Customer Lifetime Value) | Market Basket Analysis
- How to build AI applications
- How to use streamlit
- How to apply the concepts of AI in a real world web application
- How to host a AI web application
Build AI Machine Learning Apps Using Streamlit and Python Course Requirements
- None. Concepts and Python are covered extensively to assist those who are new to Python & AI.
Build AI Machine Learning Apps Using Streamlit and Python Course Description
Simulated intelligence scene is advancing quick, however these are still early days for AI. The focal point of AI has been more on building models and breaking down information, while clients were requesting fresh yields and self-utilize intelligent applications. It isn’t so much that the information science and AI people group didn’t know about these necessities.
In synopsis, end clients needed a straightforward web application to see the aftereffects of AI calculations and information researchers needed a stage to construct AI web applications effectively and quicker. Streamlit tended to both these requirements consummately.
I will show how to assemble a medical care AI application (and not many different models) in under 50 lines of code utilizing streamlit stage. This covers AI/ML code just as code for the application including the UI. We will begin with the functionalities of streamlit and afterward cover how to fabricate and have web applications.
For the individuals who are new to AI, Machine Learning, Deep Learning, Natural Language Processing (NLP) and Exploratory Data Analysis (EDA) are remembered for the program. Python is likewise covered widely to help the individuals who are searching for an update on python subjects or 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 career to AI.