Bhavya Shingariadvancedideamechanics.hashnode.dev·Dec 8, 2024Principal Component Analysis(PCA) in PythonYou will learn about PCA and how it can be leveraged to extract information from the data without any supervision using two popular datasets: Breast Cancer and CIFAR-10. Principal component analysis (PCA) is a linear dimensionality reduction techniqu...10 likesPca
govinda takstudy-pcaclassification-breast-cancer.hashnode.dev·Nov 28, 2024Comparative Study: PCA & Classification in Breast Cancer DetectionPCA-Based Classification for Breast Cancer Detection Early detection of breast cancer can significantly improve patient outcomes, making accurate diagnostic tools essential. Machine learning (ML) has revolutionized medical diagnostics by providing p...1 likeMachine Learning
Anix Lynchgozeroshot.dev·Nov 5, 2024Part 4: 10 Advanced Topics in ML and Optimization with Math Notation Friendly Explained1. Matrix Factorization (e.g., Singular Value Decomposition) Matrix Factorization is a technique used to decompose a matrix into simpler, constituent matrices, often revealing useful properties or patterns in the data. One of the most common methods ...LDA
Anix Lynchgozeroshot.dev·Nov 5, 2024Part 1: 11 Basic Machine Learning Techniques with Math Notation Friendly Explained1. Linear Regression Linear Regression is one of the simplest techniques for predicting a continuous outcome by modeling the relationship between an independent variable and a dependent variable with a straight line. Key Concept:The goal of linear re...#Regression
Riya Boseblogbyriyabose.hashnode.dev·Sep 27, 2024Cracking the Code: Mastering Dimensionality Reduction Techniques in Machine LearningIntroduction In machine learning, we often work with datasets containing a large number of features or variables. While having more data might seem beneficial, high-dimensional datasets can lead to overfitting, increased computational costs, and redu... #DimensionalityReduction
Arbash Hussaincckeh.hashnode.dev·Sep 9, 2024A Step by Step Guide to Principal Component Analysis (PCA) in Machine LearningIntroduction Welcome back to the eighth blog post in our Machine Learning series! Today, we're diving into Principal Component Analysis (PCA), a powerful tool for dimensionality reduction. PCA simplifies complex datasets while keeping as much informa...104 readsMachine LearningDimensionality Reduction
Retzam Tarleretzam.hashnode.dev·Jul 22, 2024Hands-on with Unsupervised Learning modelsHello 🤗, We'll continue where we left off and round up unsupervised learning in this chapter. We have extensively learned about unsupervised learning in the previous chapter, we learned about K-Means clustering and Principal Component Analysis (PCA)...principal component analysis
Adeniran Emmanuelemmanueladeniran.hashnode.dev·Jul 18, 2024Guide to Principal Component Analysis in Data ScienceOrigin of PCA Approach of PCA How to do PCA When is PCA used What PCA is and is not Advantages and Disadvantages of PCA Metric of Evaluation After PCA, what Next? Case Study of the Cocktail recipe Dataset Origin of PCA PCA was first develo...1 likePca
Suraj Karkisavvysuraj.hashnode.dev·Jun 28, 2024Anomaly Detection Using Linear ModelBefore I start, let's have some motivation: "Cry. Forgive. Learn. Move on. Let your tears water the seeds of your future happiness." Steve Maraboli This is the third lesson of the Anomaly Detection lecture series. In this lesson, we will see how ...Anomaly DetectionMachine Learning
Kishar Nathkishar.hashnode.dev·Apr 15, 2024What is PCA in Machine learning?PCA is a dimensionality reduction technique we use in Data science. PCA is a unsupervised learning technique, meaning it does not rely on labeled data. It has several application like Image compression, Data visualization and Exploratory data analysi...4 likesMachine Learning
