Rakesh Kushwaha | Web Developer

Hi, I'm Rakesh Kushwaha.

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Self-driven, quick starter, passionate programmer with a curious mind who enjoys solving a complex and challenging real-world problems.

About

A Web Developer with a passion for Front-End Development and crafting beautiful and responsive user interfaces with HTML, CSS, and JavaScript.

I am an Information Technology Grad Student at Dr. Rammanohar Lohia Avadh University Ayodhya. I enjoy problem-solving and coding. Always strive to bring 100% to the work I do. I have worked on technologies like Java, MySQL, MongoDB, HTML, CSS, JavaScript, C, C++ during my bachelor's. I have completed Web Development & DSA course from Apna College which helped me strengthen my experience in Java, MySQL, and MongoDB. I am passionate about developing complex applications that solve real-world problems impacting millions of users.

Languages: C, Python, JavaScript.
Databases: MySQL, MongoDB.
Libraries: NumPy, Pandas
Web Tech:HTML/CSS, React.js, Node.js, Express.js, Tailwind CSS, Bootstrap.
Tools & Technologies: Visual Studio Code, GitHub.

Detail-oriented Web Developer with a liitle experience in Development. I am adept in Java, MySQL, MongoDB, Computer Vision.

Looking for an opportunity to work in a challenging position combining my skills in Software Engineering, which provides professional development, interesting experiences and personal growth.

Current Focus: Accessibility // React // Design Systems

Projects

                
Quiz Web-App
                  A quiz playing web app based on Django
                
AccomplishmentsTools: Django, HTML, CSS, Bootstrap, SQLite, Heroku
Register/login to the web app(with OAuth-based Google Sign-In).
Play Quiz and see the leaderboard

Blog Web-App
                  A simple and extensible blog web-app based on Flask.
                
AccomplishmentsTools: HTML, CSS, Bootstrap, Flask, SQLAlchemy, Postgresql, Python
Users can view posts and contact the admin via Contact Page.
Admin can Add, Delete, Update posts.

Visual Question Answering
                  An attention-based classification model that aims at generating an answer for a given input image.
                
AccomplishmentsIncorporated Convolution Neural Networks (CNN) for extracting image features and Long Short Term
                    Memory for extracting question
                    embeddings.
Tested the model on the COCO dataset, abstract scenes images, and got 69% overall accuracy on the
                    VQA evaluation metric.

Head Counting System
                  A system that calculates the attendance of the class from a panoramic image of a live classroom.
                
AccomplishmentsUsed Singular Value Decomposition for image compression; applied various image processing
                    techniques and morphological operations to
                    detect the number of heads.