Tag: Probability and Statistics

>> Confidence Intervals

>> GMMs for Clustering

>> Introduction to the Student’s t-distribution

>> Importance of Statistics in Machine Learning

>> Gaussian Mixture Models

>> Understanding the Monte Carlo Simulation

>> Statistics: Correlation vs. Regression

>> Algorithm for Online Outlier Detection in Time Series

>> Maximum Likelihood Estimation

>> What’s the P99 Latency?

>> Shuffling an Array

>> Introduction to Gibbs Sampling

>> Statistical Independence

>> Bayes’ Theorem

>> Probability: Joint vs. Marginal vs. Conditional

>> Calculating the Average of a Set of Circular Data

>> Random Variables

>> Calculating the Odds of a Team Winning a Sports Match Given Full History

>> What Are Image Histograms?

• Image Processing

>> What Is Feature Importance in Machine Learning?

>> Random Sample Consensus Explained

>> The Mahalanobis Distance

>> Sampling From the Exponential Distribution

>> Median of a Matrix With Sorted Rows

>> Non-repeating Random Number Generator

>> How to Calculate the Runtime Percentage Improvement

>> Robust Estimators in Robust Statistics

>> What Is the Difference Between Artificial Intelligence, Machine Learning, Statistics, and Data Mining?

>> What Is a Random Walk?

>> The Effects of the Depth and Number of Trees in a Random Forest

>> The Monty Hall Problem

>> The Importance of Central Limit Theorem

>> Outlier Detection and Handling

>> Streaming Median

>> Intuitive Explanation of the Expectation-Maximization (EM) Technique

>> Choosing the best q and p from ACF and PACF plots in ARMA-type modeling

>> NLP’s word2vec: Negative Sampling Explained

>> How to Improve Naive Bayes Classification Performance?

>> Correlated Features and Classification Accuracy

>> A Simple Explanation of Naive Bayes Classification