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Creating a flawless winning strategy in a Casino (BlackJack) using Data Science?
The article explains interesting mathematical & probability concepts for Blackjack which can be applied in Casino.Explained in simple english with examples
Tavish Srivastava 26 Apr, 2017
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TensorFlow 101: Understanding Tensors and Graphs to get you started in Deep Learning
TensorFlow is the popular library of deep learning. This article describes the basics of tensors and graphs and why tensors is important for tensorflow.
Guest Blog 24 May, 2020
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How I created a package in R & published it on CRAN / GitHub (and you can too)?
This a tutorial is on how to create a package in R and publish it on CRAN & Github. It provides you hands-on experience in creating package yourself.
saurav kaushik 22 Mar, 2017
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Imbalanced Data : How to handle Imbalanced Classification Problems
Learn how to tackle class imbalance in machine learning. Explore techniques, examples, and methodologies to improve model performance!
Guest Blog 17 Dec, 2024
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Conditional Probability and Bayes Theorem in R for Data Science Professionals
Learn about conditional probability and Bayes theorem in this comprehensive article. Improve your understanding of data science algorithms.
Dishashree Gupta 04 Nov, 2024
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What is Linear Programming? Definition, Methods and Problems
Discover the fundamentals of linear programming and explore its definitions, methods, applications, and common problems in our article.
Analytics Vidhya 07 Apr, 2025
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How to build Ensemble Models in machine learning? (with code in R)
Ensemble models are used to combine various machine learning models / algorithms to create a better model. This includes boosting, bagging
saurav kaushik 25 Jun, 2019
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Basics of Probability for Data Science explained with examples in R
This is an introductory guide on probability. It explains random variables, binomial distribution, z-score, central limit theorem & many more with examples
Dishashree Gupta 16 Jul, 2024
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Comprehensive & Practical Inferential Statistics Guide for data science
This guide explains inferential statistics for data science in simple and practical manner. This includes t-tests, hypothesis testing, ANOVA & Regression
NSS 06 Mar, 2025
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Introduction to Structuring Customer complaints explained with examples
This article describes how machine learning can be used for understanding customer complaints.It has been explained with the help of examples & codes
Yogesh 12 Feb, 2017
