# Tagml

## Principal Component Analysis (PCA) Program in Python from Scratch

Principal Component Analysis (PCA) is a machine learning algorithm for dimensionality reduction. It uses matrix operations from statistics and algebra to find the dimensions that contribute the most to the variance of the data. Hence, reducing the training time. For…

## Apriori Algorithm Program in Python from Scratch

Apriori is an algorithm for frequent item set mining and association rule learning over the given dataset. It works by identifying the frequent individual items in the dataset and extending them to larger and larger item sets as long as those item sets…

## K Means Clustering Program in Python from Scratch

K-means clustering is a machine learning algorithm that is used to partition the data into K clusters in which each data belongs to the cluster with the nearest mean. KMC works by calculating the distance of each data in the…

## Linear Regression Program in Python from Scratch

Linear regression is a machine learning algorithm in which a best scalar response is established according to the variables. This scalar has the least error and can be used for prediction tasks. Linear regression works by finding the best values…

## K Nearest Neighbors Program in Python from Scratch

K-nearest neighbors is a classification algorithm that is used to classify a given test data according to the surrounding data. KNN works by calculating the distance of the test data with all the given data and selecting the first K…

## Naive Bayes Classification Program in Python from Scratch

Naive Bayes classifiers are a family of “probabilistic classifiers” based on Bayes’ theorem with strong independence between the features. They are among the simplest Bayesian network models and are capable of achieving high accuracy levels. Bayes theorem states mathematically as:P(A|B) = ( P(B|A) * P(A) )/…