The 3 types of machine learning (that every data scientist should know). Here's 3 months of research in 3 minutes. Let's go! 1. The 3 Fundamental Types of Machine Learning: Supervised Learning, Unsupervised Learning, and Reinforcement Learning. Let's break them down. 2. Supervised Learning: Supervised Learning maps a set of inputs (features) to an output (target). There are 2 types: Classification and Regression. 3. Classification: Identifying the category that something belongs to. Often I use Binary Classification for lead scoring to get a class probability (the probability from 0 to 1 of how likely the rowwise observation belongs to a class). Think non-buyer or buyer. 0 or 1. Binary Classification. 4. Regression: Predicting a continuous value. I commonly use Regression for predicting future values of sales demand. It's a special type of regression called Forecasting. 5. Unsupervised Learning: Learning from unlabelled data. 2 main types I use are clustering and dimensionality reduction. K-means is the most common clustering algorithm I use, often for clustering customers based on their similarities. I use PCA to reduce the number of columns so other supervised machine learning algorithms run more efficiently and to visualize clusters. 6. Reinforcement Learning: The idea is that the software learns to take actions based on accumulation of reward. This is the underlying concept of "AI" or Artificial Intelligence, where the software learns to think. 7. Learning Roadmap (based on real life): I highly recommend learning how to apply concepts 1 to 5 to business applications. I use these all day every day. Number 6 Reinforcement Learning I have never used Reinforcement Learning, but it's a powerful concept. Down the road I may take a stab at it and report back. Skip it until I know more (unless there is a specific application you need it for). === Need help improving your data science skills? I'd like to help. Here's how: 👉 My Free 10 Skills Webinar: I put together a free on-demand workshop that covers the 10 skills that helped me make the transition to Data Scientist: learn.business-science.io/free-rtrack-ma… 👉 Learn ChatGPT for 10X Faster DS Projects: I have a live workshop where I'll share how to use ChatGPT for Data Science (so you can complete projects 10X faster): learn.business-science.io/registration-c… If you like this post, please reshare ♻️ it so others can get value (follow me, 🔥 Matt Dancho 🔥 for more data science concepts).
@mdancho84 Reinforcement learning is hard. Lots of math
@mdancho84 If I may know, is Federated learning a Reinforcement ?
@mdancho84 great resource! def check out @LightningAI for setting up easily reproducible environments for your course participants
@mdancho84 Thanks for sharing this insightful breakdown of the fundamental types of machine learning! Your explanations are clear and easy to follow.