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k8sOperator
oumkale
Investigate-a-Dataset-of-No-show-Appointments
Dataset collected information from 100k medical appointments and is focused on the question of whether or not patients show up for their appointment. A number of characteristics about the patient are included in each row. ●My study emphasized the need for more research for a better understanding of the problem. I made recommendations for prompting patients about their upcoming appointments, helping patients get transportation to healthcare facilities and making efforts to ensure better communication between the patients and the healthcare providers to understand the complex interplay between personal, systemic and financial(Scholarships) barriers in completing appointments.mayadatahackathon
hackathonRepute
WebDev
Here are some practice codings during konnecxions .CareerChela
Program_cpp
Programming solved at CodeChef CodeForcescharthub.litmuschaos.io
front-end for litmus community chartsJP-Morgan-Chase-co-Intern
Assignment
DictionaryMayadata
WordPopulation_data
Explore-US-Bikeshare-Data
Python script code to import US bike share data computing descriptive statistics.Geeks-For-Geeks-Work
Titanic_Dataset
React-Google-Analytics-Dashboard
React Google Analytics Dashboardtest-python
e2e-test.github.io
AI-Debating-System
monsterweb
Udemy Courseproject
Web ApplicationComplete-Critical-Path-Managment
A complete Program using C++ code for Finding critical path, slack times, ES, EF, LS, LF, Predecessor matrix, Successor matrix and so all.... Graph algo is also ready but will update soon.notes
Test-a-Perceptual-Phenomenon-of-Stroop-effect
In this project, I investigated a classic phenomenon from experimental psychology called the Stroop Effect. little bit about the experiment, create a hypothesis regarding the outcome of the task, then go through the task yourself. Look at some data collected from others who have performed the same task and will compute some statistics describing the results. I have interpreted results in terms of your hypotheses.Model-Evaluation-and-Validation
The Boston housing market is highly competitive, and I want to be the best real estate agent in the area. To compete with my peers, I decide to leverage a few basic machine learning concepts to assist me and a client with finding the best selling price for their home. Luckily, I have come across the Boston Housing dataset which contains aggregated data on various features for houses in Greater Boston communities, including the median value of homes for each of those areas. My task is to build an optimal model based on statistical analysis with the tools available. This model will then be used to estimate the best selling price for your clients' homes.Love Open Source and this site? Check out how you can help us