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MohsseniMahdi/README.md

Hi there! I'm Mahdi Mohsseni 👋

🚀 About Me

I am a Data Scientist with a strong background in Physics (PhD), currently transitioning into the field of Artificial Intelligence and Machine Learning. My expertise lies in leveraging mathematical and statistical models to extract meaningful insights from complex datasets. I am passionate about problem-solving, predictive modeling, and working with real-world data to drive impactful decisions.

I am currently attending the Data Science and AI Bootcamp at Le Wagon Amsterdam, where I am refining my skills in machine learning, deep learning, NLP, and data engineering.

🔬 My Technical Skills

  • Programming Languages: Python, SQL, MATLAB, Fortran
  • Machine Learning & AI: Scikit-learn, TensorFlow, Keras, PyTorch
  • Data Analysis & Visualization: Pandas, NumPy, Matplotlib, Seaborn, Plotly
  • Deep Learning: Neural Networks, LSTMs, CNNs, Transformers
  • NLP: SpaCy, NLTK, Word2Vec, LDA, Hugging Face Models
  • Time Series Analysis: ARIMA, Prophet, LSTMs
  • Big Data & Cloud: Google Cloud Platform (GCP), AWS (Basics), PySpark
  • Software & Tools: Git, Docker, Streamlit, Flask, FastAPI, MySQL, OpenCV, SQLite, Mathematica, COMSOL, Lumerical

📚 Recent Projects

🔹 Credit Card Fraud Detection & Stock Market Anomaly Detection (Final Project @ Le Wagon)

  • Developing a real-time anomaly detection system for credit card transactions and stock prices.
  • Deploying a web application to display model predictions and insights.
  • Using machine learning & deep learning techniques for fraud detection and financial forecasting.

🔹 House Prices Prediction (Kaggle Competition)

  • Implemented advanced regression techniques to predict house prices.
  • Optimized a Neural Network model to improve performance.
  • Feature engineering, data cleaning, and hyperparameter tuning.

🔹 Airline Passenger Satisfaction Analysis

  • Built a classification model to predict passenger satisfaction.
  • Utilized NLP and sentiment analysis on passenger reviews.

🔹 Spam Email Classification (NLP & Machine Learning)

  • Trained a Multinomial Naive Bayes model for spam detection.
  • Implemented TF-IDF vectorization and preprocessing techniques.

📫 Connect with Me

🎯 Current Goals

  • Expanding my expertise in MLOps & Model Deployment.
  • Working on real-world AI applications in finance and fraud detection.
  • Seeking opportunities to collaborate on open-source projects.

⚡ Fun Fact

I want to combine sports with analytics! 🏋️‍♂️📊

🛠️ Languages and Tools

Bash Docker GCP Git MySQL OpenCV Pandas Python PyTorch Scikit-Learn Seaborn Selenium SQLite TensorFlow Mathematica COMSOL MATLAB Fortran Lumerical

📌 Let's connect and innovate together! 🚀

Pinned Loading

  1. anomguard anomguard Public

    Data Science Final Project -- Credit Card Fraud Detection Stock market anomalies detection

    Jupyter Notebook 1

  2. anomguard_web anomguard_web Public

    Python

  3. Titanic_Survival_Prediction Titanic_Survival_Prediction Public

    The default branch is considered the “base” branch in your repository, against which all pull requests and code commits are automatically made, unless you specify a different branch.

    Jupyter Notebook