This Repository consists of different kinds of Machine Learnnig models, which are coded in Python.
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Supervised Learning:- In this kind of model, target label is used while training the model. E.g:- Predicting the housing prices of new houses, provided some sample about existing price of houses and some features which impact the housing price
- Regression Techniques
- Neural Networks
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Unsupervised Learning:- Here we have a un labeled data, meaning we want to classify data into various groups but we are not sure based on training data which class each data set belongs to.
- Clustering:- Unsupervised learning can be done by seperating data into set of clusters or groups based on similarity score between different points. Similar data points can be clustered into similar groups.
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Reinforcement Learning:- In this kind of learning the model needn't be aware of how the system works, rather model learns when given +ve or -ve rewards based on it's action and stores the state information for future actions.
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