NLP Workshops and Pipeline Architecture

• Hosted NLP workshops for clients, including interactive labs and demos.
• Architected an NLP pipeline to extract audio and text signals for ML algorithms.
• Provided technical analysis and consultancy for NLP projects.
• Delivered presentations on NLP advancements and applications.

In the corporate sector, text data flows swiftly, emanating from diverse sources in various formats, destined for multiple endpoints and actions. This continuous stream of data necessitates management through structuring, making it easy to interpret and analyse, and ultimately directing it to the appropriate user or applying the insights obtained. I utilised several large language models (LLMs) streamline and enhance this process:

• A question-answering LLM, enabling users to inquire about the content of each document within the flow.
• A summarization LLM, offering a concise overview of each document.
• An NLP model for sentiment analysis, determining the sentiment of each document.
• An NLP model that calculates an absolute similarity score among all documents.
• Clustering, which groups similar documents together and simultaneously identifies outlier documents.

In the dynamic realm of banking, ensuring effective anomaly detection is paramount. Utilising my expertise in state-of-the-art ML algorithms and advanced Deep Learning techniques, I tackled this imperative at Deutsche Bank, a globally recognized leader in financial services. The solution involved several critical stages:

• Identifying relevant data from various sources.
• Researching and testing optimal Machine Learning algorithms for tabular data analysis.
• Exploring and validating appropriate Deep Learning models for extracting insights from textual data (Natural Language Processing).
• Integrating the resulting models into the rigorous banking environment, complete with all necessary software engineering components: Python, Object-Oriented Programming, Algorithm Design and Complexity, Deployment, and more.

• Developed NLP pipeline for generating videos from URLs.
• Implemented a conversation quality metric using Python and FastAPI.
• Deployed solutions via Docker on private Amazon servers.
• Developed an internal user interface dashboard in JavaScript.
• Fine-tuned GPT-neo for conditional text generation.

• Developed ML Miners on the Bittensor network for Tao and dTao cryptocurrency.
• Managed a team of ML developers on Subnet 44 “Scorevision”.
• Achieved first place consistently by training and optimizing computer vision models.
• Implemented real-time tracking of football players and pitch key points from video footage.
• Trained Yolo models for miners and Clip for validators.