Machine Learning Basics Answered!

In this article we will answer few basic questions in Machine Learning(ML) for beginners to get started! This article is meant to be concise for quick reference.

1. What is Machine Learning?

Machine learning is the science of getting computers to act without being explicitly programmed

This basically means that an algorithm gets better with experience without requiring human intervention to explicitly write code for it.

2. What are the types of Machine Learning Algorithms?

1. Supervised Learning:

Examples of Supervised Learning include Linear Regression, Logistic Regression, Decision Trees etc.

2. Unsupervised Learning:

Examples of Unsupervised Learning includes clustering techniques.

3. Reinforcement Learning:

3. What is Overfitting and how to handle it?

Few things can be done to handle overfitting:

  1. Adding more data
  2. regularization
  3. In Neural Networks, reducing the number of layers or using dropout technique helps.

4. Split ratio of data (Train, Cross-Validation, Test)

To conclude, I hope this article helps answer few questions about ML and let me know if you want part 2!

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An enthusiastic learner and a budding writer!

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