3:30 PM - 6:30 PM (IST)
3:00 PM - 6:00 PM (PKT)
10:00 PM - 13:00 PM (GMT)
13:00 - 16:00 (TSI)
About This Event
Welcome to our Machine Learning Model Training and Deployment Crash Course, we are glad to see you with us!
In this training, theoretical information such as how to build a data science project, which steps does it consist of, what are the data preparation processes are mentioned. Then, an end-to-end example machine learning project with a real-world data set is built using Python programming language and its outputs are analyzed and evaluated. The trained model, after all, will be open to the visitors to be used while being visualized on the web using the Python library called Streamlit. Streamlit is very easy to grasp yet efficient to display all the required output of the model based on the according argument inputs of the user. While not using a single line of web development, and using completely Python throughout the course, you will learn how to interact with the web and deploy your own custom models in the future!
Feel free to ask your questions via Machine learning hub on Global AI Hub Community.
You can check most frequently asked questions about this course.
• Steps of Machine Learning Project
• Random Variables
• Data Preprocessing
• Exploratory Data Analysis
• Train-Test Split
• Evaluation of Models
• Building Machine Learning Project with Real Life Dataset
• Display text, data, charts, media, interactive widgets, code, progress bar and status
• Control flow
• Add widgets to sidebar
• Lay out your app
• Placeholders, help, and options
• Final Project: “Custom trained model deployment and usage by the visitors/members”