How Artificial Intelligence is related to Machine Learning
AI is a field of computer science that is focused on building smart machines to perform activities using human-like intelligence.
Machine learning is a branch of AI which allows computers to automatically learn and improve their accuracy using data and algorithms to imitate how humans learn without needing to be programmed.
Methods used in Machine Learning
- Supervised Learning In this machine learning technique, every training sample from the dataset has a corresponding label or an output value associated with it.
Unsupervised Learning
The training samples are not labeled. Machine learning algorithms are therefore used to analyze the unlabeled data and eventually discover the underlying patterns of data without needing human intervention.Semi-supervised Learning
The training uses a smaller labeled data set to guide classification and feature extraction from a larger, unlabeled data set.Reinforcement Learning
The model learns what actions to take through trial and error.
Traditional Algorithm Models Vs Machine Learning
Traditional models solve a problem by taking the problem and a program e.g. algorithm or code as inputs for the model.
In Machine learning we solve or predict problems by using historical data and desired results for the model.
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