Data Science Archives

Machine Learning With ClickHouse: Logistic Regression

Introduction In the earlier blog article, we have seen the basics of Linear Regression and how to perform linear regression on data present in ClickHouse. In this article, let us look at an example of […]

Configuring Skipping Indexes in ClickHouse

Machine Learning with ClickHouse: Linear Regression

Vijay Anand

Introduction ClickHouse is quite a popular and capable columnar data store for real-time analytics on petabytes of data. While the ClickHouse database is frequently used to run analytical queries, it is still possible to perform […]

Data Science in ClickHouse: Normal Distributions and t Distributions

Shiv Iyer

Introduction The normal distribution and t-distribution are two of the most commonly used probability distributions in statistics. They are used to model the distribution of continuous variables, such as heights, weights, and test scores, and […]

How to Implement the Black-Scholes Model in ClickHouse?

How do Data Scientists use Black-Scholes model on ClickHouse?

Shiv Iyer

Introduction The Black-Scholes model is a mathematical formula used to estimate the price of European-style options, which are financial contracts that give the holder the right, but not the obligation, to buy or sell an […]

Implementing Chebyshev's Inequality in ClickHouse

Data Science in ClickHouse: How to implement Chebyshev’s Inequality?

Shiv Iyer

Introduction Chebyshev’s inequality is a statistical theorem that provides a bound on the probability that a random variable deviates from its mean by more than a certain number of standard deviations. Specifically, it states that […]

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