Shubham Thapa

Data Scientist

https://talent.gravityer.com/shubham-thapa

Open Source Evangelist .

Key Strengths

Demonstrated experience with various machine learning models (regression, classification, unsupervised learning).
Practical application of deep learning for image classification (Covid-Pneumonia-Normal Classifier).
Experience with Kaggle competitions, indicating problem-solving skills and ability to work with real-world datasets.
Exposure to NLP and reinforcement learning (AI-trading-bot).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio shows a strong interest in AI/ML applications, particularly in health tech and finance, which aligns with innovative and data-driven cultures. The diversity of projects suggests a proactive and self-driven individual. However, the lack of team-based project descriptions or collaborative experience makes it difficult to fully assess cultural fit.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.

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Projects

Health-Tech

June 14, 2021 – December 26, 2021

Official source code for Health Tech , a health care service provider which uses artifical intelligence to tackle the problems .

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mu745511

June 12, 2021 – March 26, 2023

mu745511 — GitHub repository

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Covid-Pneumonia-Normal-Classifier_99-accuracy_98-f1score

April 2, 2021 – October 1, 2023

This reposository contains a deep learning model to predict a patient is suffering from covid or pneumonia or the person doesn't suffer from any of those disease using there chest X ray , I have used classical transfer learning method with a state of the art pretrained model ( resnet200d ) as a backbone and fine tuned its final layers . The model shows some excellent results with a 98% f1 score and 99% accuracy in a test set .

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OSIC-pulmonary-fibrosis-

October 7, 2020 – August 8, 2021

Silver rank top 4% in Kaggle competition OSIC pulmonary fibrosis solution

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AI-trading-bot-using-deep-Q-learning-

August 23, 2020 – August 23, 2020

AI-trading-bot-using-deep-Q-learning- — GitHub repository

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NLP-CATboost-XGboost

August 18, 2020 – August 18, 2020

NLP-CATboost-XGboost — GitHub repository

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Unsuperwised-leraning-k-means-and-heirarchial-clustering-

August 18, 2020 – August 18, 2020

Unsuperwised-leraning-k-means-and-heirarchial-clustering- — GitHub repository

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Classification-models-MACHINE-LEARNING-

August 15, 2020 – August 15, 2020

Classification-models-MACHINE-LEARNING- — GitHub repository

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Regression-Models-Machine-Learning-

August 15, 2020 – August 15, 2020

Regression-Models-Machine-Learning- — GitHub repository

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titatnic-kaggle-

August 11, 2020 – August 11, 2020

titatnic-kaggle- — GitHub repository

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Key Strengths

Demonstrated experience with various machine learning models (regression, classification, unsupervised learning).
Practical application of deep learning for image classification (Covid-Pneumonia-Normal Classifier).
Experience with Kaggle competitions, indicating problem-solving skills and ability to work with real-world datasets.
Exposure to NLP and reinforcement learning (AI-trading-bot).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.

Shubham Thapa

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit