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OFI
Data Scientist
June 13, 2026 – Present
Neuro-Genetic-disorder-prediction
November 20, 2022 – February 15, 2023
Using ANN for prediction of neuro genetic disorder
View ProjectLSTM-network-for-Named-Entity-recognition
November 11, 2022 – January 5, 2023
LSTM network for Named Entity recognition
View ProjectRNN-for-Character-level-language-modeling
November 10, 2022 – January 8, 2023
RNN-for-Character-level-language-modeling — GitHub repository
View ProjectImage-classification-transfer-learning
October 29, 2022 – November 5, 2022
Transfer learning implementation using VGG16 model to classify images
View ProjectOptimizing-neural-networks
October 1, 2022 – October 10, 2022
Optimizing neural networks using L2 regularization, Dropout, data augmentation and early stopping.
View ProjectLinear-regression-with-stochastic-gradient-descent
September 19, 2022 – September 27, 2022
Implement linear regression with (i) stochastic gradient descent. and (ii) stochastic mini-batch gradient descent. Comparing the results
View ProjectObject-dectection-using-YOLO
August 31, 2022 – September 7, 2022
YOLO is an acronym that stands for You Only Look Once. We are employing Version 5, which was launched by Ultralytics in June 2020 and is now the most advanced object identification algorithm available. It is a novel convolutional neural network (CNN) that detects objects in real-time with great accuracy. This approach uses a single neural network to process the entire picture, then separates it into parts and predicts bounding boxes and probabilities for each component. These bounding boxes are weighted by the expected probability. The method “just looks once” at the image in the sense that it makes predictions after only one forward propagation run through the neural network. It then delivers detected items after non-max suppression (which ensures that the object detection algorithm only identifies each object once)
View ProjectAttendance-system-using-Facial-Recognition
August 3, 2022 – February 2, 2023
Attendance-system-using-Facial-Recognition — GitHub repository
View ProjectDeep-Learning-Workshop---Furniture-Detection
June 2, 2022 – June 6, 2022
Furniture Detection using YOLOv5
View ProjectCultural Fit Analysis
The candidate's project portfolio indicates a strong interest and self-driven learning in data science and machine learning. The projects are diverse within the ML/DL domain, suggesting adaptability and a proactive approach to skill development. However, the lack of team-based projects or professional experience beyond a single current role makes it difficult to fully assess cultural fit. The projects are all personal, which is common for an entry-level candidate, but limits insight into collaboration and communication styles.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.