**Data Scientist | Deep Learning & NLP | GenAI | MLOps **

With knowledge in Deep Learning, NLP, and AI, I work across the entire AI pipeline—from data collection to model deployment. My experience includes developing and fine-tuning neural networks like RNNs, and transformers (e.g., BERT, GPT) for applications in NLP, and predictive analytics. I specialize in transforming data into actionable insights and building robust, end-to-end AI solutions for impactful, real-world use.

• AI & Machine Learning: Deep Learning, NLP, Statistical Modeling
• Modeling Techniques: RNNs, Transformers (BERT, GPT), LSTM, GRU
• Languages & Libraries: Python (PyTorch, TensorFlow, Keras, Scikit-learn), SQL
• Data Processing: Pandas, NumPy, ETL, Web Scraping, Data Cleaning & Preprocessing
• Visualization: Matplotlib, Seaborn, Plotly, Power BI, Tableau
• NLP Capabilities: Text Classification, Named Entity Recognition, Sentiment Analysis, Embedding Techniques (Word2Vec, GloVe, FastText)

• Languages: Python, SQL, Java, C++, C#
• Libraries/Frameworks: PyTorch, TensorFlow, Keras, Hugging Face Transformers, NLTK, Spacy, Scikit-learn, Pandas, NumPy
• Cloud & MLOps: Docker, Git, MLflow, Jupyter Notebooks, VS Code
• Databases: MySQL, PostgreSQL
• Visualization & Reporting: Power BI, Tableau, Google Looker, IBM Cognos, Dash

• BSc in Computer Science and Engineering

  • American International University, Bangladesh
  • Expected Graduation: December 2025
  • Pursuing core skills in AI and Data Science through coursework, projects, and hands-on experience in database systems, machine learning, and NLP.

• IBM Data Analyst Professional Certificate

  • Completed May 2024
  • Comprehensive training in data analysis with Excel, SQL, and Python, covering data visualization, ETL, and creating interactive dashboards.
  • Credentials 1 credentials 2
    

• Unintended Bias in Toxicity Classification Link

  • This project aims to solve the Jigsaw Unintended Bias in Toxicity Classification problem from a Kaggle competition hosted by Jigsaw and Google's Conversation AI team. The objective is to build machine learning models that can detect toxicity in online conversations while minimizing unintended bias, particularly with regard to identity terms.

• ML project to demonstrate CI/CD model Link

  • Simple ML project in using CI/CD model. Fully project implementation is more focused than ML model development.

• IBM Capstone Project: Stack Overflow Job Survey Link

  • Analyzed developer trends and predicted future trends using Python, SQL, Cognos and looker. Results in PowerPoint and Jupyter Notebook

• Email: lutfulkabir1757@gmail.com
• LinkedIn: Md. Lutful Kabir

Looking forward to connecting and collaborating on AI, deep learning, or NLP projects!

Happy coding! 😊