Machine Learning (Research) Engineer with 2+ years of industry and academic experience.

• 🌍  I'm based in Canada
• ✉️  You can contact me at [email protected] (Email Header: Github Connection)
• 🧠  I'm learning • Topics in Natural Language Processing and Recommedation Systems • Advanced Topics in Computer Vision
• 🤝  I'm open to collaborating on • Computer Vision (Object Recognition or Detection or Tracking, Motion Estimation, Instance or Semantic Segmentation, GAN techniques, Real-time surveillance systems, Image Retrieval, and Restoration) • Natural Language Processing (NLP) (Topic Modelling, Sentiment Analysis, Text generation) • Recommendation System (Sequential Recommendation) • Learning Techniques (Ensemble, Active, Transfer Learning)
• ⚡  Let's talk about F1

Technical Stack:

1. Programming Languages: Python, MATLAB, C++, Java
2. Databases: SQL, PostgreSQL, MySQL, MS SQL, MongoDB Elasticsearch, Neo4j
3. Machine Learning (Python) Packages Data Analysis: Numpy, Pandas, SciPy Data Visualisation: Matplotlib, Seaborn, Plotly Computer Vision/ Deep Learning: TensorFlow, Keras, OpenCV, Scikit-learn, Scikit-Image, PyTorch Natural Language Processing: NLTK, Spacy, HuggingFace Model and Data Monitoring: MLFlow, Weight and Biases (W&B), DVC, Evidently
4. Web Technologies: HTML, CSS, JavaScript, Flask, Streamlit
5. Methodologies: Agile/Scrum Methodology, Object-Oriented design, Software Development Lifecycle (SDLC)
6. DevOps/MlOps: CI/CD, Git, Docker, Grafana, Apache Kafka, Apache Spark, Airflow, PyTest, Kubernetes,
7. Computing, Embedded Boards, and Cloud Platforms: CUDA, NVIDIA Jetson boards, Raspberry Pi models, AWS, Azure
8. Documentation and Version Control: LaTeX, Git, Github

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