Github Diptisanap Salaryprediction

Github Diptisanap Diptisanap Config Files For My Github Profile Contribute to diptisanap salaryprediction development by creating an account on github. From sklearn.linear model import linearregression from xgboost import xgbregressor [ ].

Github Diptisanap Salaryprediction Salary prediction using linear regression \n a webpage is developed using flask framework and deployed on heroku platform.\nthe below picture is preview of webpage\n. 👩‍💻 experienced python developer & machine learning engineer with hands on experience and a robust educational foundation in artificial intelligence. my dedication to ongoing learning fuels my drive for innovation in this ever evolving field with a dynamic and results oriented approach. Predict your placement salary (lpa) from cgpa using a flask scikit learn app with data driven trends, clean ui, and model transparency. this repository contains a python based program designed to calculate employee salaries. The goal is to predict the salary of data related positions based on location, company review and job title. job titles can be categorized based on the words they contain such as "director",.

Github Diptisanap Salaryprediction Predict your placement salary (lpa) from cgpa using a flask scikit learn app with data driven trends, clean ui, and model transparency. this repository contains a python based program designed to calculate employee salaries. The goal is to predict the salary of data related positions based on location, company review and job title. job titles can be categorized based on the words they contain such as "director",. Contribute to diptisanap salaryprediction development by creating an account on github. {"payload":{"allshortcutsenabled":false,"filetree":{"":{"items":[{"name":"templates","path":"templates","contenttype":"directory"},{"name":"procfile","path":"procfile","contenttype":"file"},{"name":"readme.md","path":"readme.md","contenttype":"file"},{"name":"app.py","path":"app.py","contenttype":"file"},{"name":"model.pkl","path":"model.pkl","contenttype":"file"},{"name":"requirements.txt","path":"requirements.txt","contenttype":"file"},{"name":"salary data.csv","path":"salary data.csv","contenttype":"file"}],"totalcount":7}},"filetreeprocessingtime":4.2761379999999996,"folderstofetch":[],"reducedmotionenabled":null,"repo":{"id":537779131,"defaultbranch":"main","name":"salaryprediction","ownerlogin":"diptisanap","currentusercanpush":false,"isfork":false,"isempty":false,"createdat":"2022 09 17t10:52:34.000z","owneravatar":" avatars.githubusercontent u 107847530?v=4","public":true,"private":false,"isorgowned":false},"symbolsexpanded":false,"treeexpanded":true,"refinfo":{"name":"main","listcachekey":"v0. The salary prediction app forecasts employee salaries based on years at the company, satisfaction level, and monthly hours worked. it uses a cleaned dataset and applies machine learning models like linear regression, support vector regression, and random forest regressor, with hyperparameter tuning done via gridsearchcv for improved accuracy. Import pandas as pd [ ] # step2 : import data salary = pd.read csv(" github ybi foundation dataset raw main salary%20data.csv") [ ] # step 3 : define target (y) and features (x) y.

Github Diptisanap Wine Quality Prediction Contribute to diptisanap salaryprediction development by creating an account on github. {"payload":{"allshortcutsenabled":false,"filetree":{"":{"items":[{"name":"templates","path":"templates","contenttype":"directory"},{"name":"procfile","path":"procfile","contenttype":"file"},{"name":"readme.md","path":"readme.md","contenttype":"file"},{"name":"app.py","path":"app.py","contenttype":"file"},{"name":"model.pkl","path":"model.pkl","contenttype":"file"},{"name":"requirements.txt","path":"requirements.txt","contenttype":"file"},{"name":"salary data.csv","path":"salary data.csv","contenttype":"file"}],"totalcount":7}},"filetreeprocessingtime":4.2761379999999996,"folderstofetch":[],"reducedmotionenabled":null,"repo":{"id":537779131,"defaultbranch":"main","name":"salaryprediction","ownerlogin":"diptisanap","currentusercanpush":false,"isfork":false,"isempty":false,"createdat":"2022 09 17t10:52:34.000z","owneravatar":" avatars.githubusercontent u 107847530?v=4","public":true,"private":false,"isorgowned":false},"symbolsexpanded":false,"treeexpanded":true,"refinfo":{"name":"main","listcachekey":"v0. The salary prediction app forecasts employee salaries based on years at the company, satisfaction level, and monthly hours worked. it uses a cleaned dataset and applies machine learning models like linear regression, support vector regression, and random forest regressor, with hyperparameter tuning done via gridsearchcv for improved accuracy. Import pandas as pd [ ] # step2 : import data salary = pd.read csv(" github ybi foundation dataset raw main salary%20data.csv") [ ] # step 3 : define target (y) and features (x) y.

Github Diptisanap Breast Cancer Prediction The salary prediction app forecasts employee salaries based on years at the company, satisfaction level, and monthly hours worked. it uses a cleaned dataset and applies machine learning models like linear regression, support vector regression, and random forest regressor, with hyperparameter tuning done via gridsearchcv for improved accuracy. Import pandas as pd [ ] # step2 : import data salary = pd.read csv(" github ybi foundation dataset raw main salary%20data.csv") [ ] # step 3 : define target (y) and features (x) y.