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Machine Learning

What is Machine Learning?

Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy.


Machine learning is a way for computers to learn and make decisions on their own, without being specifically programmed for every single task.

Just like how humans learn from experience, a machine learning system uses a large amount of data to recognize patterns and make predictions or decisions. For example, a machine learning system could look at a lot of pictures of dogs and learn what a dog looks like, and then be able to recognize a dog in a new picture it hasn't seen before.

Machine learning can be broken down into three main parts: input data, a model, and an output. Input data is the information that the machine learning system learns from, like pictures or text. The model is the set of rules that the machine learning system uses to make predictions or decisions based on the input data. And the output is the final result, like a prediction or a decision.

Overall, machine learning is a way for computers to learn and make decisions on their own, based on patterns in data.

Types of ML Algorithms

There are so many algorithms that it can feel overwhelming when algorithm names are thrown around and you are expected to just know what they are and where they fit.

These learning algorithms are usually classified into the following four types:

  1. Supervised Learning

  2. Unsupervised Learning

  3. Semi-supervised Learning

  4. Reinforcement Learning

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