As a Machine Learning Engineer, Data Engineer, and AI Enthusiast, I specialize in creating innovative solutions that harness the power of data and AI technologies.
- π Currently focused on: Developing state-of-the-art deep learning models for Natural Language Processing and Computer Vision applications.
- π Engaging with: Advanced topics such as Reinforcement Learning and the latest advancements in AI technologies.
- π€ Open to: Partnerships on projects that intersect Machine Learning, AI, and Data Engineering.
- Machine Learning: , XGBoost, LightGBM,CatBoost
- Deep Learning: ,Keras, ,MXNet,
- Data Science: Pandas, NumPy, SciPy, Statsmodels
- Data Visualization: Tableau, Matplotlib, Seaborn, Plotly,Bokeh
- NLP: BERT, GPT-3, LSTM, RNN, CNN
- Computer Vision: U-Net, ResNet, VGG16, EfficientNet, YOLO
- Generative Models: GANs, VAEs
- Big Data Tools: Hadoop, Apache Spark, Dask, Hive, Flink,
- Cloud Platforms: ,,
- MLOps & Deployment: , , , , CircleCI, Travis CI, MLflow, Airflow, Kubeflow
- Databases: , , , ,
- Data Warehousing: Amazon Redshift, Google BigQuery, Snowflake
- ETL Tools: Apache Airflow, Talend, Apache NiFi
Title | Description |
---|---|
NLP with Transformers | Developed advanced text classification models utilizing BERT for sentiment analysis and topic classification. |
Time Series Forecasting | Designed robust forecasting models employing LSTM, ARIMA, and Prophet to predict stock prices. |
End-to-End ML Pipeline on AWS | Engineered a scalable ML pipeline for customer churn prediction utilizing AWS services and CI/CD methodologies. |
Real-Time Data Pipeline | Architected a high-performance ETL pipeline for processing streaming log data using Apache Kafka and Spark. |
I am eager to engage in meaningful conversations about innovative projects, ideas, and opportunities. Feel free to connect with me through the following platforms:
I love exploring the intersection of technology and art. When I'm not coding, you might find me experimenting with creative projects or participating in hackathons! π