From cdabf3ddce6ff62a9e245ff66c12220754e4f341 Mon Sep 17 00:00:00 2001 From: Nic Tolentino Date: Thu, 30 Jul 2026 22:24:32 +1000 Subject: [PATCH] Fix typos in ML introduction --- .../w1-ch2-supervised-vs-unsupervised-ml.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Course 1 - Supervised Machine Learning/Week 1 - Intro to ML/w1-ch2-supervised-vs-unsupervised-ml.md b/Course 1 - Supervised Machine Learning/Week 1 - Intro to ML/w1-ch2-supervised-vs-unsupervised-ml.md index eff3cd2..0298646 100644 --- a/Course 1 - Supervised Machine Learning/Week 1 - Intro to ML/w1-ch2-supervised-vs-unsupervised-ml.md +++ b/Course 1 - Supervised Machine Learning/Week 1 - Intro to ML/w1-ch2-supervised-vs-unsupervised-ml.md @@ -27,7 +27,7 @@ There are 3 main types of Machine learning ### Superivsed learning > It refers to algorithms that learn `x` to `y` or **input** to **output** mappings. > -> The key characterstic of superivsed learning is that you give your learning algorithm examples to learn from, which includes the right answers (`y`) for a given input (`x`), and is by seeing correct pairs of input `x` and desired output label `y` that the learning algorithm eventually learns to take just the input alone without the output label adn gives a reasonably accurate prediction or guess the output. ~ *Andrew Ng* +> The key characterstic of superivsed learning is that you give your learning algorithm examples to learn from, which includes the right answers (`y`) for a given input (`x`), and is by seeing correct pairs of input `x` and desired output label `y` that the learning algorithm eventually learns to take just the input alone without the output label and gives a reasonably accurate prediction or guess the output. ~ *Andrew Ng* In Supervised learning, the algorithm maps the input data with output labeled data and guess the output on new input based on the mapping.