Work History
Education
Skills
Projects
Timeline
BusinessAnalyst
Sameek Bhoir

Sameek Bhoir

Sydney,NSW

Work History

Research Intern

National Institute of Industrial Engineering (NITIE)
05.2020 - 08.2020
  • Analyzed and researched the impact of Covid-19 on communications using statistical learning & ‘pandas’ library in Python
  • Conducted literature reviews to identify relevant research articles and support project objectives.
  • Made use of 'Tableau' for data visualization through various plots, charts, and graphs.


Education

Master of Data Science -

Macquarie University
06-2025

Bachelor of Data Science -

SP Jain School of Global Management
01.2022

Skills

  • Languages: Python, R, SQL
  • Frameworks: Pandas, Numpy, Keras, Seaborn, TensorFlow
  • Tools: Tableau, Apache Hadoop, Powerpoint, Power BI
  • Platforms: Google Colab, Jupyter Notebook, MongoDB, Neo4j, Fujitsu AutoML
  • Soft skills: Report writing, Time management, Analytical thinking, Teamwork and collaboration

Projects

  • Spam e-mail detection: Built a Spam e-mail detector, which classifies incoming e-mails into two sections: 'Spam' and 'not Spam'. A TensorFlow based deep learning model helps classify these emails. This is a sequential model with three Embedding Layers to learn featured vector representations of the input vectors. LSTM layer to identify useful patterns in the sequence. The final layer is the output layer which outputs probabilities for the two classes. This model detects spam e-mails with about 97.5% accuracy.
  • AWS Deepracer: Practiced and used AWS SageMaker and trained a Reinforcement learning model for a self-driving car. The goal was to make an accurate and fast self-driving car. https://youtu.be/YliKkN45J1M
  • Emotion detection: A large dataset of human faces with various emotions were trained using convolutional neural network (CNN) to recognize various emotions using Keras. To predict emotion in real-time, the live video from a webcam is fed into a network which detects faces and predicts the emotions.
  • Traffic density estimation: This project accurately counts vehicles within designated areas in video frames to evaluate traffic flow. A pre-trained YOLOv8 model is used to evaluate baseline performance on the COCO dataset for vehicle detection purposes.

Timeline

Research Intern

National Institute of Industrial Engineering (NITIE)
05.2020 - 08.2020

Bachelor of Data Science -

SP Jain School of Global Management

Master of Data Science -

Macquarie University
Sameek Bhoir