- Data Compression via Dimensionality Reduction: 3 Main Methods - Dec 10, 2020.
Lift the curse of dimensionality by mastering the application of three important techniques that will help you reduce the dimensionality of your data, even if it is not linearly separable.
Compression, Dimensionality Reduction, LDA, PCA, Python
- How to Prepare Your Data - Jun 30, 2020.
This is an overview of structuring, cleaning, and enriching raw data.
Data Preparation, Data Preprocessing, Dimensionality Reduction, Missing Values, Outliers
- Dimensionality Reduction with Principal Component Analysis (PCA) - May 21, 2020.
This article focuses on design principles of the PCA algorithm for dimensionality reduction and its implementation in Python from scratch.
Dimensionality Reduction, numpy, PCA, Python
- Diffusion Map for Manifold Learning, Theory and Implementation - Mar 25, 2020.
This article aims to introduce one of the manifold learning techniques called Diffusion Map. This technique enables us to understand the underlying geometric structure of high dimensional data as well as to reduce the dimensions, if required, by neatly capturing the non-linear relationships between the original dimensions.
Data Preparation, Data Science, Dimensionality Reduction, Feature Engineering, Machine Learning
7 Steps to Mastering Intermediate Machine Learning with Python — 2019 Edition - Jun 3, 2019.
This is the second part of this new learning path series for mastering machine learning with Python. Check out these 7 steps to help master intermediate machine learning with Python!
7 Steps, Classification, Cross-validation, Dimensionality Reduction, Feature Engineering, Feature Selection, Image Classification, K-nearest neighbors, Machine Learning, Modeling, Naive Bayes, numpy, Pandas, PCA, Python, scikit-learn, Transfer Learning
- What Is Dimension Reduction In Data Science? - Jan 31, 2019.
An extensive introduction into Dimension Reduction, including a look at some of the different techniques, linear discriminant analysis, principal component analysis, kernel principal component analysis, and more.
Data Science, Dimensionality Reduction, Linear Discriminant Analysis, Principal component analysis
- Must-Know: What is the curse of dimensionality? - Apr 18, 2017.
What is the curse of dimensionality? This post gives a no-nonsense overview of the concept, plain and simple.
Dimensionality Reduction, High-dimensional, Interview Questions
