Kevalsakhiya – Medium

Kevalsakhiya

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The Deep Hub

Bias-Variance Tradeoff

Bias, Variance, and Error in Machine Learning Models

Aug 23

Bias-Variance Tradeoff

Aug 23

Kevalsakhiya
in
The Deep Hub

What Is Perceptron?

The Building Block Of Neural Networks

Aug 12

What Is Perceptron?

Aug 12

Kevalsakhiya
in
The Deep Hub

Understanding Classification Metrics (Part-3)

ROC Curve and AUC-ROC

Jul 20

Understanding Classification Metrics (Part-3)

Jul 20

Kevalsakhiya
in
The Deep Hub

Understanding Classification Metrics (Part-2)

Precision, Recall, F1 score

Jul 17

Understanding Classification Metrics (Part-2)

Jul 17

Kevalsakhiya
in
The Deep Hub

Understanding Classification Metrics (Part-1)

Accuracy and Classification Matrix

Jul 14

Understanding Classification Metrics (Part-1)

Jul 14

Kevalsakhiya

Handling Missing Data: A Detailed Answer on How to Handle Missing Data (Part-2)

Univariate Imputation, Multivariate Imputation (KNN and Iterative Imputation)

Jun 20

Handling Missing Data: A Detailed Answer on How to Handle Missing Data (Part-2)

Jun 20

Kevalsakhiya

Handling Missing Data: A Detailed Answer on How to Handle Missing Data (Part-1)

Missing Completely at Random, Missing At Random, Missing Not At Random

Jun 12

Handling Missing Data: A Detailed Answer on How to Handle Missing Data (Part-1)

Jun 12

Kevalsakhiya

Best Practices For Data Cleaning: Polishing Data for Optimal Results.

Data is like a lake; the cleaner it is, the more you can see what's underneath. This article will discuss the best practices for cleaning…

May 29

Best Practices For Data Cleaning: Polishing Data for Optimal Results.

May 29

Kevalsakhiya

Hands-On Data Cleaning Using Pandas: Transforming Phone Data for Analysis

Data Cleaning

May 26

Hands-On Data Cleaning Using Pandas: Transforming Phone Data for Analysis

May 26

Kevalsakhiya

Kevalsakhiya

he/him

I’m python developer with 5 years of experience in data science and data engineering . I write articles about data science topics and technology.

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