Full Stack Developer (Python, Django, Flask and Vuejs)
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photobook
June 7, 2024 – June 7, 2024
An application to post and share photos with your friends
View Projectecommerce_app
January 14, 2022 – January 14, 2022
A E-Commerce application developed using Django Framework.
View Projectself_analysis
January 21, 2020 – January 21, 2020
Flask application for logging financial and food data.
View Projectmovie_recommendation_engine
March 30, 2018 – April 6, 2018
This is a simple movie recommendations web model, which uses collaborative filtering to recommend movies.
View Projectmovie_review_classifier
February 28, 2018 – March 12, 2018
This ml model classifies the movie reviews entered by the audience into positive or negative opinions.
View ProjectAuto-Flask-App-Skeleton-Creator
February 27, 2018 – April 6, 2018
This simple script creates the basic structure of a flask application with virtually activated command prompt, opens sublime text editor from app root directory and also pre-installs few modules.
View Projectimage_classification
May 28, 2017 – May 28, 2017
In this project, you'll classify images from the CIFAR-10 dataset. The dataset consists of airplanes, dogs, cats, and other objects. The dataset will need to be preprocessed, then train a convolutional neural network on all the samples. You'll normalize the images, one-hot encode the labels, build a convolutional layer, max pool layer, and fully connected layer. At then end, you'll see their predictions on the sample images.
View Projectsmartcab
May 24, 2017 – May 24, 2017
In this project you will apply reinforcement learning techniques for a self-driving agent in a simplified world to aid it in effectively reaching its destinations in the allotted time. You will first investigate the environment the agent operates in by constructing a very basic driving implementation. Once your agent is successful at operating within the environment, you will then identify each possible state the agent can be in when considering such things as traffic lights and oncoming traffic at each intersection. With states identified, you will then implement a Q-Learning algorithm for the self-driving agent to guide the agent towards its destination within the allotted time. Finally, you will improve upon the Q-Learning algorithm to find the best configuration of learning and exploration factors to ensure the self-driving agent is reaching its destinations with consistently positive results.
View ProjectCultural Fit Analysis
The candidate's projects are exclusively personal, which limits insight into their collaborative work style or experience in diverse team environments. While the projects demonstrate initiative and self-learning, the lack of professional experience or team-based projects makes it difficult to assess cultural fit for a corporate environment. The projects are diverse in application (ML, web dev) but all appear to be solo efforts.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are clear but do not provide insight into collaboration, problem-solving approach, or communication style in a team setting.