Master Generative AI with 10+ Real-world Projects in 2025!
Explore essential feature scaling techniques like normalization & standardization. why feature scaling is crucial for model performance!
Confusion Matrix is the visual representation of the Actual VS Predicted values. Learn what is confusion matrix and Explore the world of Confusion Matrix!
Hyper parameter tuning is an intrinsic part of the ML development cycle. Let's see 2 Bayesian optimization techniques bayes_opt & hyperopt
This article will discuss how to do a correlation test for spatial data, especially raster data, which is the image with spatial attributes
Estimators are functions of random variables that can help us find approximate values for these parameters that data scientists must know
We all are taught to delete outliers while studying data science. In this article, we are going to see why we should not delete outliers
Explore random variables, their types (discrete, continuous, mixed), probability distributions, cumulative distribution functions.
Create a replica of a financial stock market or this can be extended to the cryptocurrency market also using Geometric Brownian Motion
Statistics is one of the key foundations of data science. You cannot move forward with data science without understanding statistics
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.
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