The Black Knight

Data Scientist

https://talent.gravityer.com/the-black-knight

Aim: To provide better solutions to others...

The Black Knight

Key Strengths

Demonstrated interest in Data Science through numerous personal projects focused on Kaggle competitions, table detection, and deep learning.
Experience with core Data Science technologies like Python, TensorFlow, and Jupyter Notebook.
Active engagement with open-source resources and tutorials (e.g., TensorFlow 2.0 tutorial, Python Tutorial, Awesome-XGBoost).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio shows a strong inclination towards self-learning and contributing to the data science community through sharing solutions and tutorials. This indicates a proactive and collaborative mindset. However, the projects are predominantly personal and tutorial-focused, which might suggest a need for more experience in team-based, production-level data science environments. The current experience as 'Data Scientist' is listed as current with a future start date, making it difficult to assess real-world team collaboration or project management experience.

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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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

awesome-table-detection-and-table-structure-recognition

July 11, 2020 – July 11, 2020

awesome-table-detection-and-table-structure-recognition

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TensorFlow-Tutorial

September 26, 2019 – September 29, 2019

TensorFlow Tutorial

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TensorFlow-2.0-tutorial

September 19, 2019 – September 21, 2019

TensorFlow 2.0 tutorial

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Tabulo

August 29, 2019 – November 24, 2022

Table Detection and Extraction Using Deep Learning ( It is built in Python, using Luminoth, TensorFlow<2.0 and Sonnet.)

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Table-Detection-using-Deep-Learning

August 8, 2019 – May 29, 2021

Table Detection using Deep Learning

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Data-Science-Competitions

August 2, 2019 – January 30, 2020

Goal of this repo is to provide the solutions of all Data Science Competitions(Kaggle, Data Hack, Machine Hack, Driven Data etc...).

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Awesome-XGBoost

January 13, 2019 – January 13, 2019

This page contains a curated list of examples, tutorials, blogs about XGBoost usecases.

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Python-Tutorial

November 26, 2018 – April 24, 2022

Python Tutorial for all for Free

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unirest-java-tutorial

September 11, 2018 – September 12, 2018

Unirest is a lightweight HTTP client library from Mashape. Along with Java, it’s also available for Node.js, .Net, Python, Ruby, etc.

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Stanford-CoreNLP-Tutorial

May 5, 2018 – May 5, 2018

Stanford-CoreNLP-Tutorial — GitHub repository

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Key Strengths

Demonstrated interest in Data Science through numerous personal projects focused on Kaggle competitions, table detection, and deep learning.
Experience with core Data Science technologies like Python, TensorFlow, and Jupyter Notebook.
Active engagement with open-source resources and tutorials (e.g., TensorFlow 2.0 tutorial, Python Tutorial, Awesome-XGBoost).

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.

The Black Knight

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit