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What are the two techniques of Machine Learning?

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Machine Learning enthusiast and computer programmer.

There are three main techniques: 1) Supervised learning 2) Unsupervised learning 3) Reinforcement learning
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There are different types of machine learning: 1. Supervised learning which has classification and regression algorithms. 2. Unsupervised learning which has clustering and association algorithms 3. Semi-supervised learning 4. Reinforcement learning
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Supervised learning and unsupervised learning
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Linear Regression, Neural network, Logistic Regression
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IT Professional with 5 years of experience.

There are mainly four techniques in machine learning. 1] Supervised Learning 2] Unsupervised Learning 3] Semisupervised Learning 4] Reinforcement Learning. All these techniques is depend on the which type of database you have.
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First of all, the technique is a bad term may be it types : 1. Supervised machine learning 2. Unsupervised machine learning 3. Reinforcement learning There is also a term called semi- supervised learning.
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Mainly it's supervised machine learning and unsupervised machine.
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Data Scientist with 3 years of industry experience, taught over 15000 students with 4.7 avg rating.

There are two categories: 1. Supervised Learning - In supervised learning, we tell the machine the output/result so that it can learn from it. 2. Unsupervised Learning - In unsupervised learning, the machine learns to reach a conclusive result by itself for ex. by clustering the data.
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An experienced professional in generating value through data | Machine Learnig | Data Science

I am not sure the basis of your categorization. When it comes to 'presence of target/dependent variable', as suggested in earlier answers, 'Supervised' and 'Unsupervised'. Machine Learning algorithms are varied and may be classified in many ways.
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