Machine Learning - Elite Data Science
in Hydejack
Link: https://elitedatascience.com/learn-machine-learning
What is machine learning?
- The purpose of machine learning is to teach computers how to learn from data to make decisions, or predictions
- True machine learning occurs when the computer learns to identify patterns without being programmed to
Machine learning is often referred to/labelled as many other things:
- Data Science
- Big Data
- Artificial Intelligence (AI)
- Computation Statistics
- Data Mining
- Predictive Analysis
However, while machine learning does overlap with these fields, it is one tool for data science. It is also one use of infrastructure that can handle big data
Types/Examples of machine learning
Supervised Learning
Your email provider (i.e. gmail) automatically places “dodgy” emails in your spam folder (however, this is not always perfect. Machine learning is designed to learn as you use the software, so the more messages you send to/remove from the spam folder, the better it will (theoretically) be)
Unsupervised Learning
Marketing & advertising companies use behavior and demographic indicators to segment/separate their customers into targeted groups. This allows them to market different offers/products to different people. Because some people may like iPads and some may prefer Sony tablets, it is cheaper to determine who likes who and create smaller advertising campaigns for each group, rather than creating multiple campaigns for everyone.
Reinforcement Learning
A computer and camera that are part of a self-driving car interact with the road. Other cars can learn how to navigate a city based on this
Why learn machine learning?
- Massive global demand
- Data is power
- Fun & mentally demanding
—– Thanks for reading this post. If you’d like to have a look at our notes (as we’re learning ML too!) and projects, click on the “Projects” link in the sidebar.
Liam Arbuckle, Chairman ACoRD Robotics
www.larbuckle.tech
www.allianceofdroids.org.au