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About Me
Data Scientist @ FARFETCH
Expertise: Data Science, Deep Learning, Machine Learning, Software Engineering
As a data scientist at Farfetch, I focus on creating advanced recommendation systems that enhance the e-commerce experience. By leveraging deep insights into consumer behavior and utilizing tools like Python and PyTorch, I aim to optimize digital shopping through innovative, data-driven solutions.
My expertise extends beyond recommendation engines. I am actively involved in projects focusing on Large Language Models (LLMs), Natural Language Processing (NLP), and Generative AI. These initiatives aim to redefine the future of e-commerce through groundbreaking applications of data science.
Keep an eye on my blog for in-depth discussions on these subjects. I'm excited to share upcoming projects that highlight the practical application of theoretical knowledge in data science.
What I'm Up To
Currently Working On
I am currently exploring the froōntiers of Large Language Models (LLMs), focusing on open-source platforms. My work involves understanding these models' capabilities and limitations, how they can be applied, and potential improvements. I'm learning through various online resources, notably from experts like Sebastian Raschka (with the book Build a Large Language Model From Scratch), Eugene Yan, and Andrej Karpathy.
Reading List
I recently began studying the book "Deep Learning" by Chris and Hugo Bishop. I'm really excited to deepen my knowledge and am especially curious to explore the intricacies of deep learning and its impact on modern AI applications.
On the non-technical side, I'm currently reading "Slow Productivity" by Cal Newport.
Personal
As a federated football player, I'm gearing up for the upcoming season, which kicks off in August. My training routine is designed to enhance endurance, speed, and strength, ensuring that I'm fully prepared to excel on the field. Beyond football, I have a passion for exercise, whether it’s running, walking, or weight training. These activities not only keep me in top physical condition but also fuel my overall well-being and performance.
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RAG with LlamaIndex, Elasticsearch and Llama3
Implement Q&A using a RAG technique (Retrieval Augmented Generation) with Elasticsearch as a vector database
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Exploring OpenELM The Intersection of Open Source and High Efficiency in AI
My analysis of OpenELM An Efficient Language Model Family with Open-source Training and Inference Framework, showcasing how Apple is pushing the boundaries of AI efficiency and accessibility.
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RAG with LlamaIndex, Elasticsearch and Llama3
Implement Q&A using a RAG technique (Retrieval Augmented Generation) with Elasticsearch as a vector database
tags:
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LoRA and DoRA Implementation from Scratch
A implementation from LoRA and DoRA from scratch using PyTorch.
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Large Language Models with MLX 🚀
A Python-based project that runs Large Language Models (LLM) applications on Apple Silicon in real-time thanks to Apple MLX.