Summary Applying Machine Learning Algorithms in Real-Life
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Course
Machine Learning
Institution
Machine Learning
Dive into the practical applications of machine learning with this hands-on course designed to bridge the gap between theory and real-world implementation. This course is tailored for individuals who want to understand how machine learning can be applied to solve specific problems and drive innovat...
Applying Machine Learning Algorithms in Real-Life Business Problems
Gradient Boosting for Competitive Predictions
Gradient Boosting is a popular machine learning algorithm used for
regression and classification tasks.
It works by building an ensemble of weak prediction models, typically
decision trees, in a sequential manner.
The key idea is to combine the predictions of multiple weak models to
produce a more accurate overall prediction.
Gradient Boosting can be used to improve the performance of existing
machine learning models by reducing bias and variance.
Classification: Logistic Regression and K Nearest Neighbors
Logistic Regression and K Nearest Neighbors (KNN) are two popular
machine learning algorithms used for classification tasks.
Logistic Regression is a linear model used for binary classification
problems.
It works by modeling the probability of a data point belonging to a
particular class, using a logistic function.
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