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Data Engineer/ Data Scientist
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HSBC
Data Scientist
June 19, 2026 – Present
deep-learning-uncertainty
October 20, 2020 – October 20, 2020
deep-learning-uncertainty — GitHub repository
View ProjectDeep_Learning_Recommender_System
September 28, 2020 – October 19, 2020
You can train a neural network with user ratings or purchases, and use it to make recommendations; deep learning can be very good at recognizing patterns in a way similar to how our brain may do it. It's good at things like image recognition and predicting sequences of events.Neural networks are fundamentally matrix operations and there are already well-established matrix factorization techniques for recommender systems that fundamentally do something similar. In SVD for example, we find matrices that we multiply together using weights that are learned from stochastic gradient descent, it's almost the same thing, just thought of in a different way. So yeah, you could think of recommender systems as looking for patterns, just very complex ones based on the behavior of other people. So a matrix factorization can be modeled as a neural network. I think the main reason to experiment with applying neural networks to recommender systems is that it lets us take advantage of all the rapid adva
View Projectpython_basics
September 10, 2020 – October 3, 2020
Python For Beginner. Basic Python Tutorial
View ProjectArtificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials
September 10, 2020 – December 8, 2022
Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials — GitHub repository
View Projectsagemaker-python-sdk
September 5, 2020 – September 5, 2020
sagemaker-python-sdk — GitHub repository
View Projectdata-science-from-scratch
August 18, 2020 – August 18, 2020
data-science-from-scratch — GitHub repository
View Projectpython-training_3_day
July 13, 2020 – October 19, 2020
python-training 3 day training used for ramping up people to Python, pandas and other libraries
View ProjectCultural Fit Analysis
The candidate demonstrates a strong interest in data science and machine learning through numerous personal projects. The breadth of technologies in some projects (HTML, Java, C++, Shell, Smarty) suggests a diverse technical curiosity, which could be a positive for cultural fit in a dynamic environment. However, the focus is heavily on personal projects with limited detail on collaborative aspects or team contributions, making a full assessment challenging.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric or English test results are available.