Activity
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📢 Welcome Sheen Kak to the Spyglaz AI Team! We are delighted to introduce Sheen Kak, who is joining Spyglaz AI as a Machine Learning Operations…
📢 Welcome Sheen Kak to the Spyglaz AI Team! We are delighted to introduce Sheen Kak, who is joining Spyglaz AI as a Machine Learning Operations…
Liked by Ron Sperber
Experience
Education
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Springboard
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Springboard Data Science Career Track, Certification
Description: 550+ hours of hands-on course material, with 1:1 industry expert mentor
oversight, and completion of 2 in-depth capstone projects. Mastered skills in Python,
SQL, data wrangling, data visualization, hypothesis testing, and machine learning. -
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Licenses & Certifications
Volunteer Experience
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Member
Social Saturday Squad
- Present 2 years 3 months
Social Saturday Squad is a global networking community on LinkedIn built by and for professionals looking to expand their network. Membership involves participating in weekly networking events on LinkedIn.
Projects
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Happy Customer
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See projectUsed responses from customers to survey questions to build a model to predict if the customer would be happy.
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News Aggregator Classification
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See projectUse NLP to build a model to classify a news article as business, science & technology, entertainment, or health based on the title
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Term Deposit Marketing
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See projectPredicting whether a bank customer will subscribe to a term marketing subscription
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Diagnosing Dementia from MRI scans
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See projectTook a series of MRI scans and used a convolutional neural network to predict whether the MRI scan was of someone that had no dementia, very mild dementia, mild dementia, or moderate dementia.
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Lending Club loan analysis
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See projectTook data from loans through lending club from https://www.kaggle.com/husainsb/lendingclub-issued-loans. Cleaned and prepared the data including using K-means clustering to narrow down the feature of job title. Used Random Forest , LightGBM and neural networks to attempt to classify the loans.
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Predicting Housing Prices
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See projectTook data from https://www.kaggle.com/c/house-prices-advanced-regression-techniques/ and created model to predict housing prices. Machine learning techniques involved included Linear Regression, Decision Tree regression and LightGBM regression models.
The LightGBM model was the final model used.
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