Top Rated Freelancer at Upwork
Mar 2021 - Present
As a Top Rated freelancer on Upwork, I have successfully completed over 30 projects and have received a 5-star rating on most of them with my current JSS standing at 100%. While I am unable to list all of my projects, I am proud to highlight a few of my most notable achievements.
Purpose
Client project for an AI Chatbot integrated with Chatgpt/OpenAI. That chatbot could be used for customer support, sales, and marketing. It had option to be custom trained for specific use cases by the business utilizing this chatbot. It is embeddable to any website with simple steps and had a dashboard to manage the chatbot.
Purpose
Project to Build a new and better Keyword driven & data driven framework for automation testing of web applications compared to an old one written in Java. Initial versions included UI using Python’s Tkinter library, but later shifted to a web based interface loaded from static files using Selenium. Flask was used to serve static files and handle API requests.
Purpose
This project aims to verify the location of Instagram posts. It reads the data from a file, and checks if the coordinates reside within the US. If not, it adds them to a list to verify. It then verifies the locations using Instagram, it opens the profile of user and get the coordinates. If no coordinates are found it generates them using city or country name, then if the location is not in the US, it deletes the entry from the data. At end it writes the updated data to a new file.
Purpose
Project to Encrypts contents of csv with a “key” file. It requires the file for decryption.
Purpose
Project to keep 100 random values from a csv file and randomize them, and deleting the remaining values. It was kind of getting sample data from a large dataset.
Purpose
This project had analysis task and then article writing talking about Open Data, and providing an analysis of the eviction notices on Housing and Buildings in San Francisco. The analysis was done on the dataset of eviction notices in San Francisco. The dataset was obtained from the San Francisco Open Data website. The dataset was then analyzed to find the most common reasons for eviction, the most common neighborhoods for eviction, Plot yearly graph of eviction notices, Plot population graph (10-years gap), Compare increase in eviction notices with population increase. Plot yearly graph for eviction notices per zip code, Find and plot population increase by zip code, Compare increase in eviction notices with population increase. An article was also written for it.
Purpose
This was a project to analyze the McDonald’s menu and find the ideal calorie menu for different people of different age and gender. Then it calculates calories and recommendation of ideal amount of meat, vegetables, and neutrients like carbohydrates, sugars and proteins. Finally based on above analysis just by entering a user’s age and gender, it will recommend the ideal meal for that user at that time from the McDonald’s menu. An article was also written for it.
Purpose
This project’s main purpose was to keep the screen alive (prevent sleeping) even if the user is away from the computer. It was initially built in Python, then for simplicity and ease of use it was later shifted to Visual Basic Script (Awake2), that asked for options related to functionality in start.
Purpose
This project included analyzing large datasets of bixi bikes ridership and analyzing against parameters like Date, Weather, Day/Night, Location, Pricing etc. The goal was to find the effect of these parameters on each other and how the number of rides were effected, and to get the most optimal number of bikes available at each time and season of the year, with appropriate pricing. An article was also written for it.
Purpose
Project to Login LinkedIn, search for a given query and scrape each and every company’s details from the search results one by one. The data was then saved to a CSV file, it had resume functionality and scraped a couple hundred thousand companies.
Purpose
This was a project to find the most optimal location of where to open a coffee shop in Vancouver. What it did was find a safe neighbourhood in Vancouver based on crime data provided via kaggle datasets, then show locations that are safe (based on crime data), recommend store hours based on this information, locations that are close to transit stops based on the skytrain/Rapid Transit data and locations that do not have a Starbucks location in the vicinity (pick a numeric value of say 2 km around a transit stop). Visualize all of this in a map. Crimes include Theft (Vehicle and Bicycle), Break & Enter (Residential and Commertial), Mischief, Robbery. An article was also written for it.
Purpose
This project was the first part of an application, it was an analysis on go. One had the dataset of ingredients used in each recipe and when specific ingredients were chosen, it would suggest cooking recipes that can be made using those ingredients. It would also include plotting statistics about the most ingredients purchased by famous shopping locations like Wallmart, Target. The second part would have included building an application with image detection of ingredients and the app would suggest recipes realtime while shopping.