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Achievement: Pull Sharkx2Achievement: Quickdraw

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muhammedshihab1001/README.md


Self-taught Machine Learning Engineer passionate about building intelligent systems and scalable AI solutions.

I focus on developing production-ready machine learning pipelines, deep learning models, and backend infrastructure for real-world AI applications.

Core areas of interest:

  • Deep Learning Architectures
  • Natural Language Processing (NLP)
  • Time Series Forecasting
  • Generative AI Systems
  • MLOps and Model Lifecycle Automation
  • AI Backend APIs and Deployment

Programming Languages

Python C Java C++ HTML5 CSS3 JavaScript


Machine Learning & Data Science

TensorFlow PyTorch Keras Scikit-Learn Pandas NumPy SciPy Statsmodels Matplotlib Seaborn Prophet NLTK spaCy


Transformers, LLMs & Generative AI

Transformers HuggingFace LangChain LlamaIndex RAG


Web Development & APIs

Django Flask FastAPI REST API Bootstrap

Databases

MySQL PostgreSQL

Big Data & Data Engineering

Apache Spark PySpark Hadoop Hive HDFS

MLOps & Model Lifecycle

MLflow DVC Kubeflow TFX Prometheus Grafana

Cloud & DevOps

AWS Google Cloud Azure Docker Docker Compose


Version Control, Testing & CI/CD

Git GitHub GitHub Actions Jenkins pytest Pylint

Other Tools

Anaconda Jupyter Notebook



Pinned Loading

  1. MarketSentinel MarketSentinel Public

    Production-grade ML signal intelligence engine for quantitative trading. Powers real-time XGBoost inference across 100 S&P 500 tickers, 4-agent decision governance, algorithmic drift detection with…

    Python

  2. diabetes-prediction-ml diabetes-prediction-ml Public

    End-to-end Machine Learning pipeline for diabetes prediction with SMOTE balancing, feature engineering, hyperparameter tuning, and recall optimization for medical diagnosis.

    Jupyter Notebook

  3. promptcraft promptcraft Public

    Prompt profiles that standardize and optimize AI behavior across models and use cases.

  4. adult-income-spark-ml adult-income-spark-ml Public

    End-to-end income classification pipeline using PySpark ML — preprocessing, feature engineering, and Logistic Regression on the UCI Adult Income dataset.

    Jupyter Notebook

  5. nyc-taxi-fare-prediction-pyspark nyc-taxi-fare-prediction-pyspark Public

    End-to-end taxi fare prediction on 3M+ NYC trip records using PySpark MLlib - feature engineering, cross-validation, and Random Forest regression at scale.

    Jupyter Notebook

  6. quora-duplicate-question-detection quora-duplicate-question-detection Public

    Detect duplicate questions using NLP techniques including TF-IDF + Logistic Regression, Siamese LSTM, and TinyBERT Transformers. Built using the Quora Question Pairs dataset.

    Jupyter Notebook