Every user will register using AADHAR ID and data will be fetched using AADHAR API as it will provide hassle free Sign Up . Working employees will feed their company email id for Validation and other users will feed their email ids. By using company Email ids for account validation, it will be easier to verify if a person is an employee or not, therefore increasing the Credibility of the Data available in our application related to each User . It will be much easier to club the employees according to their companies. The employee can remain anonymous by not revealing his name to others and his profile will include details related to work he/she do and respective working Hours. Each employee can give rating and his/her feedback on different topics related to company and also the work culture .

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Real Insight

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Every user will register using AADHAR ID and data will be fetched using AADHAR API as it will provide hassle free Sign Up . Working employees will feed their company email id for Validation and other users will feed their email ids. By using company Email ids for account validation, it will be easier to verify if a person is an employee or not, therefore increasing the Credibility of the Data available in our application related to each User . It will be much easier to club the employees according to their companies. The employee can remain anonymous by not revealing his name to others and his profile will include details related to work he/she do and respective working Hours. Each employee can give rating and his/her feedback on different topics related to company and also the work culture . Ratings given by employee will take into consideration, his/her designation and experience as well, so that a better experienced employee's feedback will have more significance, like an employee working for 10 years will have more effect than one working for 2 years. Rest of the feedback will include recreational activities, work burden, infrastructure and much more features like these. Being anonymous will help more and more employee's to write feedbacks without fearing about any harm. For the Users who are not employee of any company like students and other job seeking persons , it will be the best place to get the accurate information about the company as they will get the answers from the employee's of the company itself. Interactive graphs will be provided so that user can see company ratings on basis of important points as well overall satisfaction rating given by Employees of that company . If user asks some question about particular company by tagging that company, then employees of that company will get notification about that and can answers the question. It will be an elegant solution as there is no platform where user can ask and simutaneously see Details of the company and we think it will open a new Realm of Company-User interaction.

OpenCV Project on Product Placement Analysis comprising of pre-trained TF Model, Automated pipeline to train and test upcoming image inputs and annotation using Grounding DINO Algorithm

For this project we sought to use API calls to fetch and return nationwide real estate data from multiple sources and then visualize that data to illustrate how property values have changed over time. The period of time we chose to on was 2012 to 2017. Our initial source of data from Kaggle.com was converted from CSV format to JSON and loaded to MongoDB. We then employed Flask API to call the housing data and display it on an interactive map of the United States using Plotly and Chloropleth. To drill down further we included a feature allowing the user to see data on the top 5 highest values in the country or inspect value change by state.