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Description: This repository contains a basic implementation of Simple Linear Regression, a fundamental supervised learning algorithm. The project model training, and evaluation with visualizations to ...
Those stories refer to supervised learning, the more popular category of machine learning algorithms. Supervised machine learning applies to situations where you know the outcome of your input data.
There are dozens of machine learning algorithms, ranging in complexity from linear regression and logistic regression to deep neural networks and ensembles (combinations of other models). However ...
Linear regression is a simple kind of learning function, but it provides a good basis for the more advanced forms like gradient descent, which is used in feed forward neural networks.
Termed as one of the simplest supervised machine learning algorithms by researchers, this regression algorithm is used to predict the response variable for a set of explanatory variables. This ...
With the buzz around machine learning, perhaps it seems surprising that we are starting with such a standard statistical technique. In "How Not to Be Wrong: The Power of Mathematical Thinking", Jordan ...
For example, a linear regression algorithm might be best for simple numerical predictions, while support vector machines may be good for more complex tasks like image classification. Each algorithm ...
Types of Machine Learning: Supervised Learning: Involves training a model on labeled data. Regression: Predicting continuous numerical values (e.g., housing prices, stock prices). Classification: ...
Supervised learning is a powerful technique in the field of machine learning where algorithms are trained using labelled data. This means data points come with pre-defined outputs like labels or ...
This project is based on a kaggle dataset. Objective of the project is to predict the amount of carbon dioxide emitting from different cars using supervised learning techniques (specifically ...
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