- Published on
In this project, we aim to explore the famous Iris dataset, a classic example in machine learning, by visualizing its features and then applying Principal Component Analysis (PCA) to reduce dimensionality and gain insights.
All Posts
All Posts
- machine-learning (7)
- deep-learning (3)
- regression (3)
- autoencoder (2)
- keras (2)
- tensorflow (2)
- data-graph (2)
- -k-nearest-neighbors (2)
- classification (2)
- data-analysis (1)
- data-graphs (1)
- data (1)
- ai (1)
- linear-regression (1)
- logistic-regression (1)
- polynomial-regression (1)
- pytorch (1)
- pretrained (1)
- neural-networks (1)
- -pca (1)
- evaluation-metrics (1)
- Published on
This project involves the implementation of a K-Nearest Neighbors (KNN) classifier using the famous Iris dataset.- Published on
In this project, we present the evaluation of a machine learning classification model that uses the K-Nearest Neighbors (KNN) algorithm to better learn the implementation of the various metrics to evaluate a classifier.- Published on
This project presents a simple binary classification problem using logistic regression. The goal is to train a model to distinguish between two groups of data, which are centered around arbitrary points, using PyTorch.- Published on
In this project, we will explore and implement a model that uses polynomial regression to predict housing prices based on one feature of the dataset (number of rooms).