Regularization in Machine Learning

  • By Sagar Gade
  • June 1, 2024
  • Machine Learning
Regularization in Machine Learning

Regularization in Machine Learning

  • Regularization in machine learning is a set of techniques used to prevent overfitting and improve the generalization capability of a model. Overfitting occurs when a model learns to fit the training data too closely, capturing noise and irrelevant patterns that do not generalize well to unseen data.
  • Regularization techniques add a penalty term to the loss function during training, encouraging the model to learn simpler patterns that are more likely to be generalized.
# Import All Lab's

import numpy as np 
import pandas as pd 
import seaborn as sns
import matplotlib.pyplot as plt 

import warnings

# Load CSV Files 
df = pd.read_csv("C:/Users/Administrator/Desktop/SevenMentor All Data/Data Sci/csv files/50_Startups.csv")

Regularization in Machine Learning

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