mohamedziane,github

Main Areas of Interest

𝗦ummary Of Projects:

Create multiple advanced time series models using ARIMA/SARIMA for forecasting. Projects details here.
Perform frequentist statistical inference using python by utilizing many statistical concepts: probability distributions, estimation techniques, central limit theorem, confidence intervals, hypothesis testing (z-statistic, t-statistic, p-value). Projects details here.
Build Movies recommendation Engines using Tensorflow Recommenders (TFRS- Google/YouTube Hybrid based recommender). Projects details here.
Design, built and fine tune multiple supervised Classification models (Binary and multiple classifiers): Linear, logistic, Decision Tree, Random Forest, SVM and XGBoost. Project details here and here.
Create multiple clustering models using unsupervised Machine Learning: K-means. Projects detail here.
Manipulate and transform big data using MySQL, PostgreSQL, Python (sqlalchemy library) and SQLite. Project details here.
Utilize advanced Visualization skills to extract insights using: Matplotlib, seaborn, and Plotly. Projects detail here.

👇𝗖𝗢𝗥𝗘 𝗦𝗞𝗜𝗟𝗟𝗦👇

Constant Learner: Currently focused on ETL cloud engineering with Big Data.
Primary Language: PySpark, Python (NumPy, Pandas, scikit-learn, TensorFlow, keras, Scrapy, BeautifulSoup, requests, etc.).
Data Visualizations: Tableau, looker, Matplotlib, seaborn, Streamlit and Plotly.
Cloud Certified: AWS & Azure
Business Intelligence Tools: business object, AWS SageMaker, AWS EC2, Streamlit, Jupyter/Anaconda, GitHub/Git, Microsoft Excel, Microsoft Power Point and PowerBI.
Effective verbal and written communication for technical and non-technical audiences.
Passionate about working with big data and the ability to translate insights into business recommendations.
Outstanding problem solving and analytical skills.
Strong attention to detail, and excellent organization skills.

I’d love to chat further, please feel free to reach me:

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