**A sigmoid function** is a mathematical function that helps us transform a wide range of numbers into a more manageable range between 0 and 1. It’s like squishing the numbers together into a specific range.

Imagine you have a number line that goes from negative infinity to positive infinity. A sigmoid function

takes any number from this line and squeezes it into a smaller range, like squishing it between 0 and 1. It

does this in a smooth and gradual way.

**Why would we want to do this?** Well, sigmoid functions are often used in machine learning and artificial intelligence because they are helpful for representing probabilities. The output of a sigmoid function can be thought of as the likelihood or probability of something happening.

**For example,** let’s say we want to predict whether a student will pass an exam based on how many hours they studied. We can use a sigmoid function to map the number of hours studied to a probability of passing the exam. If the sigmoid function outputs a value close to 0, it means the probability of passing is very low. If it outputs a value close to 1, it means the probability of passing is very high. And if it outputs a value around 0.5, it means the probability of passing is moderate.

**So, in simple terms, a sigmoid function is a handy mathematical tool that helps us map a wide range of numbers to a more manageable range between 0 and 1, which is often used for representing**

**probabilities in various applications.**