Python REMote Interface library. Platform independent. In about 100 Kbytes, perfect for your diet.

GPU based Electron on a diet

Built by a PhD whose memory was failing, whose diet was a mess, and whose anxiety had its own agenda. Most second brain tools ignore the fact that your brain doesn't work in isolation: your body and your mental health are part of the system too. This crew handles all three: knowledge, nutrition, and mental wellness.

🤏 A collection of tiny JS libraries (under 2 kB) to put your bundle on a diet

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Personalized Genomics and Proteomics. Main diet: Ensembl, side dishes: SNPs

Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Implementation

A full-stack diet recommendation system using machine learning

R Package for Calculating Healthy Eating Index-2020 (HEI2020), Alternative Healthy Eating Index (AHEI), Dietary Approaches to Stop Hypertension (DASH), Mediterranean Diet (MED), Dietary Inflammation Index (DII), and Planetary Health Diet Index from the EAT-Lancet Commission (PHDI) for the NHANES, ASA24, DHQ, and other dietary assessments

A minimal Vim/Neovim color scheme inspired by Dieter Rams

Asset pipeline ring middleware

Webapp for tracking personal diet, sleep, and general wellness

Diet and exercise tracker... a robust Spring Boot sample application

The major reason for the death in worldwide is the heart disease in high and low developed countries. The data scientist uses distinctive machine learning techniques for modeling health diseases by using authentic dataset efficiently and accurately. The medical analysts are needy for the models or systems to predict the disease in patients before the strike. High cholesterol, unhealthy diet, harmful use of alcohol, high sugar levels, high blood pressure, and smoking are the main symptoms of chances of the heart attack in humans. Data Science is an advanced and enhanced method for the analysis and encapsulation of useful information. The attributes and variable in the dataset discover an unknown and future state of the model using prediction in machine learning. Chest pain, blood pressure, cholesterol, blood sugar, family history of heart disease, obesity, and physical inactivity are the chances that influence the possibility of heart diseases. This project emphasizes to evaluate different algorithms for the diagnosis of heart disease with better accuracies by using the patient’s data set because predictions and descriptions are fundamental objectives of machine learning. Each procedure has unique perspective for the modeling objectives. Algorithms have been implemented for the prediction of heart disease with our Heart patient data set

STL files for the NumWorks graphing calculator

A seasonal foods calendar app for a conscious and sustainable diet.

formulate diet optimization as sequence generation that produces a diet of recommended intake

Automatic cat weighing and dieting system.

This repository houses machine learning models and pipelines for predicting various diseases, coupled with an integration with a Large Language Model for Diet and Food Recommendation. Each disease prediction task has its dedicated directory structure to maintain organization and modularity.

Veganify is a modern webapp that allows you to easily scan EAN barcodes to check if a product is vegan-friendly. With a database of over 3 million products, you can quickly find out if your favorite foods and products are suitable for a vegan diet.

Source code to reproduce results of our paper "DIET: Lightweight Language Understanding for Dialogue Systems"

Carnivorous eating, paleolithic ketogenic diet and medicine, and zero carb lifestyle. Don’t bother with vegetables. Just eat meat.

IRB on a diet, for MacRuby / Ruby 1.9

A JavaScript macronutrient calculator for low-carb or ketogenic diets

Liteqube - put Qubes OS on a diet

Slim down your Docker images with the power of AI. Container Diet analyzes your images and Dockerfiles to provide actionable, context-aware optimization advice.

[CVPR 2025] Official code of "DiET-GS: Diffusion Prior and Event Stream-Assisted Motion Deblurring 3D Gaussian Splatting"

Nutrition is the main source of life and although it has been our secondary instinct to check for nutritional value in the food we eat, the effect any diet has on our body and health is consequential. From the fact which connotes the value of nutrition in our diet, springs the idea of nutri.gram. nutri.gram is a mobile application that scans the food label present in the packaged food items and draws a significant conclusion from that data regarding its edibleness for a person, the nutritional worth it adds to our diet, how much calorific value it provides per serving and much more. This application is targeted to anyone who wants to get insight into what they are feeding into their body and how understanding the nutritional value will be of tremendous aid to their overall health.

DIET Classifier mini implementation on pytorch.

Meal tracker for the Zone diet. (Reference app for Application Layering blog post)