This article is a Python copying activity record of Chapter 9, Part 3: 'Logistic Regression Model' from the book 'Introduction to Data Analysis with Bayesian Statistical Modeling using R and Stan'.

You get scalability to large datasets, flexible loss functions, and advanced convergence control for free. The only cost is adding one extra scaler to your pipeline. #MachineLearning #DataScience ...

This important work employed a recent functional muscle network analysis to evaluate rehabilitation outcomes in post-stroke patients. The research direction is relevant and supported by solid evidence ...

2.1 CT image classification Recent research in biomedical imaging has explored a wide range of classification approaches for tumor detection in different organs, including the brain, lung, colon, ...

This project analyzes loan portfolio data using Python and Machine Learning to predict loan defaults, generate business insights, and enable conversational analytics through PandasAI and LangChain. - ...

The primary challenge is to analyze unstructured restaurant metadata and customer reviews to help Zomato improve user experience and business operations. Specifically, the project aims to solve two ...