Machine learning (ML) is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
Machine learning and Artificial intelligence better ?
Artificial intelligence is all about doing human intelligence tasks but faster and with reduced error rate. Machine learning is a subset of AI that makes software applications more accurate in predicting outcomes without having to be specially programmed.
Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input to predict new output values.
You could call some machine learning methods (neural networks are examples) statistical models. Long answer: As implied by its name machine technology methods were made for software/machines while statistical methods
There are many types of Algorithms, but the fundamental types of Algorithms are:
• Inear Regression.
• Logistic Regression.
• Decision Tree.
• S.V.M.
• Naive Bayes.
• K.N.N
• K-Means.
• Random Forest.
Machine Learning Techniques:
• SUPERVISED LEARNING: Common supervised learning tasks typically implement prediction, regression, or classification.
• UNSUPERVISED LEARNING: Unsupervised learning enables a machine to explore a set of data. After the initial exploration, the machine tries to identify hidden patterns that connect different variables.
• SEMI-SUPERVISED LEARNING:
Semi-supervised learning combines techniques from unsupervised and supervised learning.
• REINFORCEMENT LEARNING;
Reinforcement learning enables a machine to interact with an environment.
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