Mathematics For Machine Learning Course
What will I learn?
Improve your Business Intelligence skills with our Mathematics for Machine Learning Course. Get stuck in to exploring data, getting good at ways to find things that don't fit in and deal with missing bits of info. Learn how to get data ready, including making it normal and sorting out things that don't fit, to make your models work better. Check out machine learning ways for time-based stuff, like decision trees and ARIMA. Get good at making features, making things work their best, and checking how good your models are. This course gives you real, top-notch skills you can use in the real world.
Apoia's Unique Features
Develop skills
Enhance the growth of the practical skills listed below
Get good with data structures: Look at and understand tricky data sets well.
Find things that don't fit: Spot things that are odd to make your data more correct and reliable.
Use time-based models: Use ARIMA and LSTM to guess what will happen accurately.
Make algorithms work their best: Use gradient descent to train models efficiently.
Make features: Create polynomial features to make your models work even better.
Suggested summary
Workload: between 4 and 360 hours
Before starting, you can modify the chapters and the workload.
- Select which chapter to commence with
- Add or remove chapters
- Increase or decrease the course workload
Examples of chapters you can include
You’ll be able to generate additional chapters similar to the examples below
This is a free course focused on personal and professional growth. It does not equate to a technical, undergraduate, or postgraduate qualification, but offers practical and relevant knowledge for your professional journey.