Blog
-
May 26, 2026
A Naive Bayes Classifier is a simple yet powerful machine learning algorithm used to classify data into categories. It’s based...
-
May 23, 2026
Bayesian_credit_risk In [ ]: Dataset source: https://www.kaggle.com/datasets/laotse/credit-risk-dataset STEP 1: LOAD THE CREDIT RISK DATASET¶ In [36]: # Import pandas import...
-
May 23, 2026
Naive_Bayes_1_email_spam_filter Naive Bayes For Email Classification¶ In [8]: import pandas as pd from sklearn.naive_bayes import MultinomialNB from sklearn.model_selection import train_test_split...
-
May 23, 2026
LDA_2_wine LDA : Reducing Dimension¶ Application of LDA in Modelling¶ In [ ]: import numpy as np from sklearn.datasets import...
-
May 23, 2026
Linear Discriminant Analysis (LDA) is a supervised machine learning technique that projects high-dimensional data into a lower-dimensional space. It maximizes...
-
May 23, 2026
Customer Segmentation Using PCA and K-Means PCA_1_Application_Kmeans-credit-card-customer-segmentation Clustering Credit Card Users¶ In this notebook, our main task is to cluster...
-
May 23, 2026
How PCA Speeds Up Model Training Time Reduces data dimensionality: PCA eliminates redundant, highly correlated features from your dataset. Decreases...
-
May 23, 2026
PCA Application Notebook Summary This notebook demonstrates how Principal Component Analysis (PCA) converts high-dimensional datasets into lower-dimensional visualizations while preserving...
-
May 23, 2026
This notebook loads the breast cancer dataset and inspects its shape, duplicates, missing values, and class balance. It separates features...
-
May 22, 2026
tut_PCA_1_implementation_using_numpy Example1) PCA 2D to 1D¶ In [1]: import numpy as np import matplotlib.pyplot as plt In [ ]: Create...
Categories
- Deep Learning (4)
- Educate (1)
- Machine Learning (23)
- Uncategorized (4)