Computer Science Engineering Student 👨🎓, Machine learning Practitioner 👨🏫 , Full Stack Dev ⚛️(React and Django).
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cisco
Data Scientist
June 16, 2026 – Present
notifications-menu-react
March 7, 2024 – March 7, 2024
notifications-menu-react — GitHub repository
View Projectdigital-course-file-students-view
May 3, 2021 – October 4, 2021
Students view for Digital-course-file-system
View Projectdigital-course-file
May 3, 2021 – October 4, 2021
Software Engineering project for helping faculty to manage courses.
View Projectyolov4_mask_detection
August 29, 2020 – September 12, 2020
This is project on mask detection, done by me and my teamate Balaji Dass for a mlh hackathon,Successfully trained yolo model with custom datasets gathred from google and kaggle.
View ProjectHandwritten-number-detection-using-ANN
April 26, 2020 – May 12, 2020
The standard example for machine learning these days is the MNIST data set, a collection of 70,000 handwriting samples of the numbers 0-9. now we predict which number each handwritten image represents.Each image is 28x28 grayscale pixels, so we treat each image as just a 1D array, or tensor, of 784 numbers.MNIST provides 60,000 samples in a training data set, 10,000 samples in a test data set, and 5,000 samples in a "validation" data set. We haven't talked about validation sets before, but their intent is to be used for model selection. So you'd use validation data to select your model, train the model with the training set, and then evaluate the model using the test data set.The training data, after we "flatten" it to one dimension using the reshape function, is therefore a tensor of shape [60,000, 784] - 60,000 instances of 784 numbers that represent each image. we define our architecture by 1 hidden layer and we use relu for activating nodes and we use 20 epochs and keep batch size
View Projectsentiment-analysis-
April 20, 2020 – April 20, 2020
this dataset is downloaded from kaggle and in this dataset containes all the customer id's and the reviews given, and whether the review is positive, negative or neutral and we need to predict which part of the sentence is reponsible for the review being positive, negative or neutral and this can be simply done by using sentiment analyzer in sklearn library but the accuracies are too low so alternatively this can be done by using lstm
View Projectsmile-detector-using-opencv
April 10, 2020 – April 10, 2020
this is a python code which uses haarcascade files for eye,face and smile detection with the help of opencv we are utilizing these haarcascade files for some face recognization and this calcluations are done on cpu and the input is obtained from the webcam the input video is fragmented into frames and these frames are converted into gray images and calculations are done on these grey images and the result is projected back into video on window with the help of opencv
View ProjectCultural Fit Analysis
The candidate's projects show a strong inclination towards personal learning and exploration in machine learning and web development. The diversity of projects, from front-end development to deep learning, indicates a broad interest. However, the 'experienceLevel' is 0, and the only listed experience is a current 'Data Scientist' role starting in the future (2026), which suggests this is a prospective or planned role rather than current professional experience. This makes it difficult to assess cultural fit based on professional work history. The personal projects align with a Data Scientist role, but the breadth of web development projects might indicate a less focused career path or a strong foundational interest in general software development.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The provided data primarily focuses on technical projects and lacks information on collaboration, problem-solving approaches, or communication styles.