/Learning-ML

I'm studying machine learning.

Learning-ML

Machine Learning:

  • ML systems learn how to combine input to produce useful predictions on never-before-seen data.
  • is a field of computer science that uses statistical techniques to give computer systems the ability to LEARN with data, without being explicitly programmed

1. Machine learning Algorithm:

  • Supervised learning (học có giám sát):

    1. is a algorithm which maps an input to an output based on example input-output pairs
    2. it infers a function from labeled training data consisting of a set of training examples
    3. là một thuật toán mà nó dựa trên các cặp dữ liệu (input, output) đã được biết, hoặc cung cấp trước đó để dự đoán đầu ra (output) của một dữ liệu mới nào đó.

  • Unsupervised learning

  • Semi-supervised learning

  • Reinforcement learning

2. Framing:

  • Regression: an regression model predicts continuous value. For example, regression models make predictions that answer questions like the following:
    • What is the value of a house in NY?
    • What is the probability that a use will click on this ad?
  • Classification: a classification model predicts discrete value. For example, classification models make predictions that answer questions like the following:
    • Is a given email message spam or not spam?
    • Is this an image of a dog, a cat, or a hamster?