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Artificial Neural Network is a set of algorithms. This article is a beginners guide to learn about the basics of ANN and its working
Bayesian decision theory refers to the statistical approach based on tradeoff quantification among various classification decisions
A normal (or Gaussian) distribution is a type of continuous probability distribution. Learn about transformation of normal distribution
Regularization is one of the most important concepts of ML. Learn about the regularization techniques in ML and the difference between them
Cross-validation is a resampling technique. This article covers various cross-validation methods in machine learning to evaluate models.
Learn effective techniques for initializing weights in neural networks to optimize model performance and convergence.
Order statistics are a useful concept in statistical science. This is an introduction to order statistics and its distribution
Create a replica of a financial stock market or this can be extended to the cryptocurrency market also using Geometric Brownian Motion
Let's understand how a confusion matrix works and how it looks with the help of an example that I will be referring to throughout the article.
Learn how to make a simpler implementation for advanced optimization algorithms in machine learning.
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