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Ridge regressions are some of the simple techniques to reduce model complexity and prevent over-fitting which may result from simple linear regression.

Apriori-Algorithm

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Upper-Confidence-Bound-UCB-

Upper Confidence Bound Algorithm

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Clustering

Fundamentals of Clustering

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KNN-Regression

KNN regression's fundamentals and parameters analysis

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Support-Vector-Machines

SVM fundamentals

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Decision_boundary_of_Logistic_Regression

decision boundary of logistic regression

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COVID-19-analysis

Naive-Bayes-Theorem

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Natural-Language-Processing

Natural Language Processing using Python

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yeartocentury

used for converting year to century

Join_Function

This Note will explain "join" function in Python.

Artificial-Neural-Network

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Sigmoid_function

how do plotting sigmoid fuction

Representation-with-a-Feature-Cross

In this exercise, you'll experiment with different ways to represent features.

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Linear_Regression_

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Joint-Data-Augmentation-and-Network-Optimization-for-Text-Recognition

Python

ATM-predictions

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Titanic-Machine-Learning-from-Disaster

using machine learning to create a model that predicts which passengers survived the Titanic shipwreck.

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tekinadem/Ridge-Regression

tekinadem

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