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Mathematics For Machine Learning Course

What will I learn?

Make your Business Intelligence skills strong with our Mathematics for Machine Learning Lesson. Go deep inside data, learn how to find things dat strange and fix data dat missin'. Learn how to clean up data, like makin' all di numbers look di same and dealin' with di strange things, so your machine learnin' go work good. Learn about machine learnin' ways for lookin' at data over time, like decision trees and ARIMA. Get good at makin' new features from di data, makin' di machine learnin' work faster, and checkin' if di machine learnin' workin' good. Dis lesson go give you di real skills you need for use machine learnin' in di real world.

Apoia's Unique Features

Accessible online course for a lifetime
Certificate aligned with educational standards
Printable PDF summaries
Online support available at all times
Select and arrange the chapters you wish to study
Set your own course workload
Instant feedback on practical activities
Study anytime, no internet required

Develop skills

Enhance your practical skills in the areas listed below.

Know data well: Look at big data and understand what e mean.

Find strange things in data: See di things dat no normal, so di data correct and reliable.

Use time series machine learnin': Use ARIMA and LSTM for guessin' what go happen in di future.

Make machine learnin' work fast: Use gradient descent for train di machine learnin' fast.

Make new features: Make new things from di data so di machine learnin' go work better.

Suggested summary

Workload: between 4 and 360 hours

Before starting, you can modify the chapters and the workload.

  • Choose which chapter to start with
  • Add or remove chapters
  • Increase or decrease the course workload

Examples of chapters you can add

You will be able to generate more chapters like the examples below

This is a free course, focused on personal and professional development. It is not equivalent to a technical, undergraduate, or postgraduate course, but it offers practical and relevant knowledge for your professional journey.