Bifalgorithm post

"Let's build your very first machine learning model step-by-step because it's actually a lot simpler than you think. First, we're going to import all of our frameworks and libraries, and then we're going to be working with this pretty tiny data set of 10 points. These data points show us how many hours somebody slept and the energy score that they reported the following day. Now, in real life, you would have way more data, and it's not going to be clean and pretty like this, but for the sake of the tutorial and the example, let's keep going. The goal here is to teach the computer to predict somebody's energy levels depending on how many hours of sleep they got. split our data into testing and training sets. X is the input, so the sleep data, and Y is the output, which is the energy score. Training set is the one that actually teaches the model, and the training set tell us how well it actually did. We're going to be using a linear regression, which is one of the simplest models that's really great to use as a baseline so that we can better understand the correlation between sleep and energy. We'll make our prediction on the test data and actually This metric is going to tell us how far our prediction was from the actual result. And I'm a very visual learner, so I like to visualize the results with a graph, and we can see the relationship here, but if you want a deeper breakdown, follow for part two, where I'll go in deeper into actually learning how we can evaluate and better understand our results."

"Let's build your very first machine learning model step-by-step because it's actually a lot simpler than you think. First, we're going to import all of our fr…