I'm Hamza, an aspiring Data & AI Engineer based in Casablanca. I'm interested in how data and AI can solve practical problems, and I learn best by building projects.
I enjoy connecting the pieces: preparing data, exploring models, and turning the results into useful applications. My goal is to grow into an engineer who can take an idea from raw data to a working product, while continuing to learn about data engineering, machine learning, and cloud technologies.
Missing values, error codes and outliers.
Imputed, capped and ready to learn from.
Learns the pattern and shows what weighed in.
A probability, a threshold, then an action.
[A short line about your profile: data, machine learning, deep learning, IoT, and what you're looking for (PFE internship, apprenticeship...).]
Reads world news (18.4 million GDELT events) and flags which suppliers are exposed through their city or the strait on their shipping route, by comparing each place with its own normal over 28 days. A full lakehouse pipeline feeds a static site that reads the data in the browser. The supplier portfolio is fictional; the events are real.
Tracks the Nantes bike-sharing network, spots empty and saturated stations, and suggests which bikes to move from where to where. A pipeline collects the open feed every 60 seconds and the interface shows the real age of the data.
A LightGBM model estimates the probability that a client defaults within 2 years and shows which factors weighed in the decision. Trained on about 150,000 clients, served by a live API.
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Three posts a week on data, AI and tech news, explained clearly and sourced.
Know what Databricks and Snowflake really changed in October, which numbers are only vendor claims, and follow a 5-step plan you can run this week.