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Finding Donors: Built an algorithm that best identifies potential donors.
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Image Classifier: Implement an image classifier with PyTorch.
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Identify Customer Segment: Apply unsupervised learning techniques to identify clusters of the population that are most likely to be purchasers of products for a mailout campaign.
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Write a Data Science Blog Post: Analyze Stack overflow data from 2017 to draw some results for questions such as "How active are developers on Stack Overflow?" "Is the developer’s salary related to their activity on Stack Overflow?" "Is the status of the user account related to user behavior? Can it be further utilized?". Accompanying blog post can be found here
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Build Pipelines to Classify Messages with Figure Eight: Build ETL and ML pipelines to classify messages sent during disasters.
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Design a Recommendation Engine with IBM: Implement recommendation techniques using data from the IBM Watson Studio platform.
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Data Science Capstone Project. Explore data from Starbucks Rewards Mobile App and implement a promotional strategy with uplift models. Accompanying blog post can be found here