Tagged python

Rebuilding evaluation calculations for recommendation systems

A lot of models work. Evaluation metrics tell us which ones work well.

Evaluation metrics describe how well a model predicts on unseen data, and are used in fine-tuning. In the Python package "implicit", the evaluation module returned errors for common metrics, such as Normalised Discounted Cumulative Gain (NDCG).

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User churn model

Predicting inactivity using activity, and the lack thereof

Digital media rely on user activity to determine marketable audiences. Being able to predict churning users allow for retention efforts to be put in place. In this project, I defined churn as a 30-day streak of a logged-out state, or 30-day streak of non-listenership.

machine-learningpythonlightgbmoptuna

Ad Request Optimisation

Increased profit margins by limiting ad requests to profitable observations.

Supply-Side Platforms manage ad space by deciding which instances of web traffic would be good to show ads to; however, not all traffic is profitable, and sending these instances to the auction (real-time bidding) can be costly.

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3-Step ETL Reporting Tool

Integrate 5 Brand Data Sources programmatically to populate reporting records.

Management makes use of spend, revenue, and eCommerce metrics to make marketing decisions. The stakeholders had a preference for tables that could be explored by date range and broken down by date.

reportingetlpythonapis

Youtube API Data Extraction

Extract video and channel data from search queries, and store them to a database.

For my first Python project, I wanted to understand popular video topics in a certain niche, and explore Youtube as a data source. One of the largest limitations to the project is the rate limit, which compelled me to consider an ETL process to avoid redundant extraction.

data-engineeringetlpythonpandassqliteapi