Skip to content
View aliduabubakari's full-sized avatar
πŸ’­
I may be slow to respond.
πŸ’­
I may be slow to respond.

Block or report aliduabubakari

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
aliduabubakari/README.md

Nerdy GIF

Twitter Badge LinkedIn Badge Medium Badge Gmail Badge

πŸ‘‹ Hi, I'm Alidu Abubakari

I'm a passionate researcher and data enthusiast specializing in Data Analytics, Cloud Computing, ETL pipelines, and AI-driven solutions.

About Me πŸ‘€

  • πŸŽ“ Currently pursuing a Ph.D. in Computer Science at University of Milano-Bicocca, focusing on semantic table interpretation, scalable data enrichment pipelines, and AI research.
  • πŸ› οΈ Completed the Azubi Data Analytics Professional Certification, and continuously expanding my expertise in data analytics, machine learning, and cloud technologies.
  • πŸš€ Experienced in building ETL pipelines, scalable data solutions, and integrating AI into real-world applications.
  • 🀝 Open to collaboration on machine learning, data engineering, and AI research projects.
  • πŸ“« Let's connect! LinkedIn

Skills βš™οΈ βš™οΈ βš™οΈ

  • Data Analytics Data Analytics
  • Machine Learning Machine Learning
  • Cloud Computing Cloud Computing
  • Cloud FinOps Cloud FinOps
  • Python Python
  • SQL SQL
  • Data Visualization Data Visualization
  • Statistical Analysis Statistical Analysis
  • Streamlit app development Streamlit App Dev
  • Gradio app development Gradio App Dev
  • NLP with Huggingface Natural Language Processing
  • FastApi FastApi

Projects πŸ“‚ πŸ“‚ πŸ“‚

  • Project 1: This is a project to forecast grocery sales for CorporaciΓ³n Favorita, an Ecuadorian grocery chain.

  • Project 2: In this project, we aim to find the likelihood of a customer leaving the organization, the key indicators of churn as well as the retention strategies that can be implemented to avert this problem.

  • Project 3: Building a machine learning (regression model) webapp for grocery sales prediction using streamlit

Articles πŸ“š πŸ“š πŸ“š

Feel free to explore my GitHub repositories to find more interesting projects and contributions.

Let's connect and collaborate to make an impact in the exciting world of data analytics and machine learning!

Profile Views

Popular repositories Loading

  1. Sepsis-Classification-with-FastAPI Sepsis-Classification-with-FastAPI Public

    This project is focused on the accurate and efficient classification of sepsis cases using the FastAPI framework. Sepsis is a critical medical condition that requires prompt identification and trea…

    Jupyter Notebook 11 4

  2. churn-prediction-with-gradio churn-prediction-with-gradio Public

    This repository contains code and resources for building a churn prediction model using machine learning techniques, and deploying it with Gradio for a user-friendly interface. Gradio is used to cr…

    Jupyter Notebook 2

  3. Streamlit-grocery-sales-prediction-app Streamlit-grocery-sales-prediction-app Public

    Building a machine learning (regression model) webapp for grocery sales prediction using streamlit

    Jupyter Notebook 2 1

  4. Azubian_forecasting_Prediction Azubian_forecasting_Prediction Public

    The objective of this challenge is to create a model to forecast the number of products purchased per week per store over the next eight weeks, for grocery stores located in different areas in the …

    Python 2

  5. California-Housing-Price California-Housing-Price Public

    The purpose of this project is to build a machine learning model of housing prices in California using the California census data. This data has features such as population, median income, median h…

    Jupyter Notebook 1

  6. Music-Recommender Music-Recommender Public

    An unsupervised learning model which analyses music genre and gives predicts genre based on Decision Tree Classifier

    Jupyter Notebook 1