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...Discuss #DimensionalityReduction
Gayathri Selvaganapathiaienthusiast.hashnode.dev·Aug 31, 2024Customer Segmentation Using Machine LearningTable of Contents Introduction Understanding the Dataset Data Wrangling and Cleaning Exploratory Data Analysis (EDA) Unsupervised Learning Techniques K-Means Clustering Principal Component Analysis (PCA) Autoencoders 6. Visualizing Custom...DiscussCustomer Segmentation, personalized experiences, technographic segmentation,
Md Shahriyar Al Mustakim Mitulmitul-shahriyar.hashnode.dev·Aug 8, 2024Machine Learning : Deep Learning - AutoEncoders (Part 31)AutoEncoders are within Unsupervised Neural Networks. AutoEncoders look like this: Auto Encoder encodes itself. That it takes some sort of inputs, put some through a hidden layer, and then it gets outputs, but it aims for the outputs to be identical...DiscussAutoencoders
Osen Muntuoseninsights.tech·Jun 13, 2024Understanding Autoencoders: Unsupervised Representation LearningAutoencoders (AEs) are a type of neural network particularly useful for unsupervised learning, where the goal is to find patterns and representations within data that doesn't come with labels. This is essential when dealing with large datasets where ...Discuss·1 likeAutoencoders
