What is Machine Learning?
You probably use it many times a day without even knowing it. Anytime you want to find out something like “how do I make a sushi roll?” you can do a web search on Google, Bing or Baidu to find out. And that works so well because their machine learning software has figured out how to rank web pages. Or when you upload pictures to Instagram or Snapchat and think to yourself, “I want to tag my friends so they can see their pictures.” Well, these apps can recognize your friends in your pictures and label them as well. That’s also machine learning. Or if you’ve just finished watching a Star Wars movie on the video streaming service and you think “what other similar movies can I watch?” Well the streaming service will likely use machine learning to recommend something that you might like.Machine learning is the science of getting computers to learn without being explicitly programmed.
Definition
Here’s a definition of what is machine learning that is attributed to Arthur Samuel. He defined machine learning as:“The field of study that gives computers the ability to learn without being explicitly programmed.”Samuel’s claim to fame was that back in the 1950s, he wrote a checkers playing program. The amazing thing about this program was that Arthur Samuel himself wasn’t a very good checkers player. What he did was he had programmed the computer to play maybe tens of thousands of games against itself. By watching what positions tend to lead to wins and what positions tend to lead to losses, the checkers playing program learned over time what are good or bad positions. By trying to get to good and avoid bad positions, this program learned to get better and better at playing checkers. Because the computer had the patience to play tens of thousands of games against itself, it was able to get so much checkers playing experience that eventually it became a better checkers player than Samuel himself.
Two Main Types of Machine Learning
The two main types of machine learning are Supervised Learning and Unsupervised Learning. Of these two, supervised learning is the type of machine learning that is used most in many real-world applications and has seen the most rapid advancements and innovation.Supervised Learning
Learn x to y or input to output mappings with labeled training data
Unsupervised Learning
Find structure or patterns in data without output labels
Supervised Learning
Supervised Machine Learning or more commonly, Supervised Learning (SL), refers to algorithms that learn x to y or input to output mappings.The key characteristic of supervised learning is that you give your learning algorithm examples to learn from. That includes the right answers, whereby “right answer” means the correct label y for a given input x.
Unsupervised Learning
In Unsupervised Learning, we’re given data that isn’t associated with any output labels y. Say you’re given data on patients and their tumor size and the patient’s age, but not whether the tumor was benign or malignant. This is unsupervised learning. We call it unsupervised because we’re not trying to supervise the algorithm to give specific outputs.Real-World Applications
Machine learning is rapidly making its way into big companies and industrial applications:Climate & Energy
Climate & Energy
Machine learning is already helping to optimize wind turbine power generation, contributing to efforts in combating climate change.
Healthcare
Healthcare
AI is starting to make its way into hospitals to help doctors make accurate diagnoses and improve patient care.
Manufacturing
Manufacturing
Computer vision is being put into factories to help inspect if something coming off the assembly line has any defects.
Communication
Communication
Each time you use voice to text on your phone or ask “Hey Siri” or “OK Google” for something, that’s machine learning in action.
Email & Security
Email & Security
When you receive an email titled “Congratulations! You’ve won a million dollars” and your email service flags it as spam - that’s also an application of machine learning.
What’s Next?
Ready to dive deeper into machine learning? Continue with our quickstart guide to get your environment set up and start learning.Quick Start Guide
Get started with Mindect and set up your learning environment
Jupyter Notebook Setup
Install the most widely used tool for ML practitioners