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...Discuss·4 likesMachine Learning
Aman .aman65823.hashnode.dev·Mar 18, 2024PCA-Principal Component AnalysisToday we learnt about the PCA What is PCA? Principal Component Analysis (PCA) in Machine Learning? Reducing the number of variables in a data collection while retaining as much information as feasible is the main goal of PCA. PCA can be mainly used f...DiscussPca
K Ahameddatailm.hashnode.dev·Jan 13, 2024Unraveling the Unseen: Revealing Hidden Patterns in Unlabeled DataUnsupervised learning is a branch of machine learning that explores patterns and structures within data without the presence of labeled outputs. Unlike supervised learning, where the algorithm is provided with labeled training data to learn and make ...DiscussMachine LearningUnsupervised learning
K Ahameddatailm.hashnode.dev·Jan 9, 2024Unveiling the Power of Dimensionality ReductionIn the vast landscape of data science and machine learning, the abundance of features within datasets presents both an opportunity and a challenge. While having a rich set of features allows models to capture intricate patterns, it also introduces th...DiscussMachine LearningDimensionality Reduction
Andrea D’Agostinodag.hashnode.dev·Nov 21, 2023Introduction to PCA in Python with Sklearn, Pandas, and MatplotlibAs data analysts and scientists, we are often faced with complex challenges due to the growing amount of information available. It is undeniable that the accumulation of data from various sources has become a constant in our lives. Data scientist or ...Discuss·41 readsData AnalyticsPca
Saurabh Naiksaurabhz.hashnode.dev·Sep 30, 2023PCA Explained: The Key to Unlocking Insights in Multidimensional DataIntroduction: In the vast landscape of machine learning, dealing with high-dimensional data is a common challenge. As datasets grow in complexity, the curse of dimensionality can lead to increased computational demands, overfitting, and difficulty in...DiscussML algorithm intuitions with essential conceptsPca
Rutvik Acharyadatamokotow.com·Jun 9, 2023Understanding Principal Component AnalysisIntroduction Hey there fellow data enthusiasts! Have you ever struggled with datasets that have too many variables? Fear not, because dimensionality reduction is here to save the day! Simply put, dimensionality reduction is the process of reducing th...DiscussData SciencePca
Bhagirath Deshani bhagirathkd.hashnode.dev·Jan 7, 2023#34 Machine Learning & Data Science Challenge 34What is Principal Component Analysis (PCA), and why do we do it? The main idea of principal component analysis (PCA) is to reduce the dimensionality of a data set consisting of many variables correlated with each other, either heavily or lightly, wh...Discuss·29 readsMachine Learning & Data Science Interview ChallengesMachine Learning
yang liyangli.hashnode.dev·Jun 17, 2022PCA by Python1.1 What's PCA? When it comes to methods of reducing dimension, PCA that is an unsupervised linear transformation technique, must not be ignored. Moreover, if you want to know the subtle relationships among data set and reduce the computational compl...Discuss·50 readsMachine Learning
