Bayesian Optimization for Hyperparameter Tuning of Deep Learning Models
to tune hyperparamters of deep learning models (Keras Sequential model), in comparison with a traditional approach — Grid Search. Bayesian Optimization Bayesian ...
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Estimating Product-Level Price Elasticities Using Hierarchical Bayesian
In this article, I will introduce you to hierarchical Bayesian (HB) modelling, a flexible approach to automatically combine the results ...
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Multiple Linear Regression Analysis | Towards Data Science
full code for this example at the bottom of this post. Multiple regression is used when your response variable Y ...
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Understanding Random Forest using Python (scikit-learn)
trees are a popular supervised learning algorithm with benefits that include being able to be used for both regression and ...
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How to Set the Number of Trees in Random Forest
Scientific publication T. M. Lange, M. Gültas, A. O. Schmitt & F. Heinrich (2025). optRF: Optimising random forest stability by ...
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Google’s New AI System Outperforms Physicians in Complex Diagnoses
going to the doctor with a baffling set of symptoms. Getting the right diagnosis quickly is crucial, but sometimes even ...
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No More Tableau Downtime: Metadata API for Proactive Data Health
In today’s world, the reliability of data solutions is everything. When we build dashboards and reports, one expects that the ...
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Mastering Hadoop, Part 3: Hadoop Ecosystem: Get the most out of your cluster
As we have already seen with the basic components (Part 1, Part 2), the Hadoop ecosystem is constantly evolving and ...
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Nine Pico PIO Wats with Rust (Part 2)
This is Part 2 of an exploration into the unexpected quirks of programming the Raspberry Pi Pico PIO with Micropython. ...
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The Gamma Hurdle Distribution | Towards Data Science
Which Outcome Matters? Here is a common scenario : An A/B test was conducted, where a random sample of units ...
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