Easy to use Python library of customized functions for cleaning and analyzing data.
100% Kotlin/Native PDF/EPUB Library (read, write, edit, create, render). Full KMP (Android, iOS, Web Wasm/JS, JVM Desktop). No expect/actuals. Supports pure rendering directly to Compose canvas. Interop views also included. Feature-rich and navigation-rich (all gestures available, text selection...etc)
Hardware 2FA TOTP authenticator
Embedded hardware (arm cortex) library to use with cmake and (arm-none-eabi-)gcc
In this repository, we would see different available libraries for Exploratory Data Analysis
Fast MCP server for Kotlin/Native Apple API lookup with local klib indexing, compact symbol cards, and on-demand metadata inspection.
Machine learning solution for insurance cross-selling optimization, achieving 89.7% ROC-AUC using an ensemble of CatBoost, LightGBM, and XGBoost models. Analyzes 11M customer records to predict vehicle insurance interest among health insurance customers.
Build a model that can predict customers' Long Term Value (LTV).
Open flash loader example project for the lpc1756 and the is25lq040b
Kotlin Multiplatform library template for quick-starts without dealing with boilerplate code
Data cleaning and Exploratory data analysis is the challenging task for everyone. Around 80% of time is taken for the data cleaning and EDA and remaining 20% is for model building and all other process. Because of it's time complexity, reasearchers introduced a more Automated libraries for perform Automated EDA and data cleaning operations with …
Build a Machine Learning model to predict the CTR(click through rate) of an email campaign based on the email campaigning information.
conducted in-depth analysis of a large dataset containing historical sales data, product attributes and store information. --> Developed and implemented machine learning models, including regression algorithms, to accurately forecast sales for different products and stores and we finally obtained a better result through random forest regression alg
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