This course talks about networks flows which are used in more obvious applications such as optimal matchings, finding disjoint paths and flight scheduling as well as more surprising ones like image segmentation in computer vision. It then proceed to linear programming with applications in optimizing budget allocation, portfolio optimization, finding the cheapest diet satisfying all requirements, call routing in telecommunications and many others. Next discussing inherently hard problems for which no exact good solutions are known (and not likely to be found) and how to solve them in practice.

A healthcare application for reminders to track health according to flow and diet during menstruation that allows users to customize the tracking of their menstrual cycles, and a diet tracking feature.

An implementation of importance sampling with normalizing flows based on (Müller et. al, 2019), implemented in Pytorch. A phase space generator based on "RAMBO on diet" (Plätzer, 2018) is included in order to be used with matrix elements generated by, for example, MadGraph 5.

Offline diet tracker with daily logs and progress graphs

Diyetisyen Yönetim Merkezi.

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Due to the improvement in people's standards of living, Obesity rates are increasing at an alarming speed, and this is reflective of the risks in people's health. People need to control their daily calorie intake by eating healthier foods. But due to our busy schedule, we lose track of our daily diets and often take the wrong food. The hard-times of following the diets is now over, we have developed a mobile application that acts as a personal companion who keeps track of our daily diets for us. Our app is tuned in such a way that it learns the user's taste and preference to recommend the right food with the right caloric content. We use Augmented Reality(AR) and our Deep Learning algorithm to increase the accuracy of food classification and predict the number of calories present in the food. This enhances the User Experience by making the user interact with our app in a fun manner. Data Science plays a crucial role in our app. Using Data Science we keep track of the User's daily food intake and represent the collected data in a graphical manner(Data Visualization). Users can also post their progress and achievements in social media platforms(Instagram, Facebook, Snapchat, etc.). we are using Bitmojis to enhance the User Interface(UI) and make the user stay in the ecosystem. As our future enhancements, we are planning to embed our app with other food ordering applications(Uber Eats, Swiggy, Dominos pizza, etc.).

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Demonstates nlp flow for diet tracker tool project

Food preferences and allergy, diet tracker application written in Vaadin Flow for the Vaadin Builder Challenge.

Farm-to-consumer price spread, processor concentration, SNAP/school lunch money flow, diet-related disease as healthcare cost driver

searching different food recipes according to dish type and diet .. code in kotlin ( mvvm , hilt , kotlin flow , room for network caching)

This is a Common Lisp implementation of the HLFLOW algorithm for maximum flows as of Dieter Jungnickel: "Graphs, Networks and Algorithms"

REACT / RAILS Application with Facebook Oath / User Login Flow for Calculating | Logging | Tracking Net Carbs against Calories and Weight while on a Ketogenic Diet

Prototype backend for my natural language diet/exercise training app. Trying out different LLM flows, sys prompts and datacleaning scripts for the nutrition db

A calm, conversion-focused yoga and wellness platform with live Zoom batches, blood-group diet intake, admin lead dashboard, and Supabase-ready inquiry flow.

REACT / RAILS Application with Facebook Oath / User Login Flow for Calculating | Logging | Tracking Net Carbs against Calories and Weight while on a Ketogenic Diet

this app to help you search your recipes according to your diet or dish type - developed using kotlin (mvvm , kotlin flow , dagger hilt , room for caching )

Analysis code for the study on low-inflammatory diet (LID) intervention in Familial Adenomatous Polyposis (FAP) patients, integrating multi-omics (flow cytometry, lipidomics, transcriptomics, proteomics) and statistical modeling.

Fit Flow is a simple front-end web application focused on physical fitness, yoga, and diet planning. It features a clean and user-friendly interface built with HTML, CSS, and JavaScript, offering sections for workout routines, yoga poses, and diet tips. Perfect for exploring front-end design and UI development!

An AI-powered diet recommendation chatbot that collects user data (age, weight, height, gender, activity level) and generates personalized meal plans. Built with a structured conversation flow and backend integration for dynamic nutrition logic.

DESISHRED is an AI-powered Indian fitness coach that calculates personalized calories, macros, meal plans, workout splits, and supplement recommendations based on user goals, diet type, and activity level. Includes a full onboarding flow and dynamic dashboard UI.

FitLifePro is a Salesforce-based CRM solution for managing memberships, trainers, workout & diet plans, and customer engagement in fitness centers. It uses Sales Cloud, Service Cloud, and Experience Cloud with custom objects, Apex, Flows, and dashboards to streamline operations and improve member experience.

MyKCLPal is a mobile health-management prototype designed using a human-centred design process to help users maintain consistent wellness habits across exercise, diet, and budgeting. The project combines user research, interaction design, and system flow modelling to translate real user needs into an intuitive app experience.

Food Recipes application, where you can browse recipes from different kinds of meals and diet types and add them to your favorite. For this, I used an MVVM architecture, ROOM Database, Coil, Retrofit, Dagger-Hilt, Coroutines, Navigation Component, DataStore Preferences, DataBinding, LiveData, Flow, DiffUtil, RESTAPI, Motion Layout, and ViewPager

This is a recreated version of the Personal Nutrition Management System developed as part of my academic learning. The project was rebuilt to improve my understanding of nutrition-based system design, user data handling, and application flow. It focuses on core functionalities like nutrition tracking and basic diet recommendations.