Hello there! I'm Anmol Jaiswal, a Senior AI/ML Engineer with a passion for transforming raw data into impactful, data-driven solutions. With extensive experience in machine learning, NLP, LLMs (Large Language Models), Generative AI (GenAI), and MLOps, I've built scalable pipelines and deployed advanced AI systems across various domains. My goal is to not only harness the power of data but also to make it actionable, ensuring businesses thrive with smart, automated solutions.

• Programming Languages:

  • Python 🐍 (primary), R 📈, SQL 💾

• AI & Data Science Frameworks:

  • Transformers, Scikit-Learn, TensorFlow, PyTorch, Hugging Face, Spark NLP

• Large Language Models (LLMs) & Generative AI:

  • GPT-4, RAG (Retrieval-Augmented Generation), BERT, RoBERTa, T5, Stable Diffusion

• MLOps:

  • Model Deployment, CI/CD Pipelines, Monitoring & Retraining, Docker, Kubernetes, MLflow, Airflow

• Big Data & Distributed Computing:

  • PySpark, Spark, Databricks, MLflow 📊

• Data Visualization:

  • Plotly, Seaborn, Matplotlib, Tableau, Power BI

• Cloud & DevOps:

  • AWS, Google Cloud, Azure, Docker 🐳, Kubernetes ☸️

• Version Control & Collaboration:

  • Git, Jupyter Notebooks, Streamlit

With expertise in LLMs, GenAI, and MLOps, I specialize in creating end-to-end scalable AI/ML solutions that encompass model development, deployment, monitoring, and retraining. By leveraging GPU acceleration and quantized models, I ensure robust, scalable, and efficient real-time data processing and insights that drive real business value.

• Spark-cum-Multi-node-GPU SentimentAnalyzer: This project implements a scalable and efficient sentiment analysis framework using PySpark, Spark NLP, and Hugging Face Transformers. It is designed to process large-scale textual data in a distributed environment, leveraging GPU acceleration, quantized models, and mixed precision techniques for faster and more accurate sentiment analysis. This framework is ideal for handling extensive datasets in real-time and producing detailed sentiment scores at both the sentence and document levels.

   from sentiment_analyzer import SentimentAnalyzer
   
   sentiment_analyzer = SentimentAnalyzer(spark)
   result_df = sentiment_analyzer.trigger_SentimentInference(df, text_column="text", sentParse=True)
   
   # Show results
   result_df.show(truncate=False)

• NLP Sentiment Analysis on Twitter Data: Implemented LSTM networks with TensorFlow to analyze sentiments, with an 88% sentiment classification accuracy.
• Dynamic Dashboard for COVID-19 Data Visualization: Created an interactive dashboard using Power BI to track and visualize the pandemic's impact globally.

I’m always open to discussing new projects, innovative ideas, or opportunities to collaborate on emerging technologies in data science. Reach out through the links above!

The projects and code hosted in my repositories serve as a showcase of my skills and are primarily intended for educational and demonstrative purposes. They do not carry any license from formal institutions unless explicitly stated.

For further information or inquiries, feel free to contact at [email protected]

Anmol Jaiswal
Senior Data Scientist | GenAI Developer | Machine Learning Engineer | Data Strategist