Learn Machine Learning

Explore Linear Regression, Neural Networks, and K-Nearest Neighbors interactively!

Explanation of Machine Learning

Machine learning (ML) is the process a device (machine) needs to go through in order to find new information (learn) and provide better results. A popular example of this would be ChatGPT, a large language model (LLM) capable of generating code, making letters, quizzes, articles, and holding a conversation with the user. Below are some examples of ML.

Linear Regression: Learning from Data

Click on the canvas to add data points. The red line adjusts to fit the data, showing how machine learning finds the best fit.

Neural Network: A Simple Perceptron

Click "Train Neuron" to simulate a simple neural network learning process. The neuron adjusts its weight based on the data.

Neuron Output:

K-Nearest Neighbors (KNN) Visualization

Click to add points to the canvas. Choose the number of neighbors (K) to classify a new point (green). The color of the point shows its predicted class.

K (Number of Neighbors)
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