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Name: Paulo Cysne

Type: User

Company: Self-employed, Senior Data Science Consultant

Bio: Senior Data Science expert

Location: Geneva, Switzerland

👋 Hi, I’m Paulo. I'm a Data Science leader based in Switzerland with lots of experience in Data Science
👀 I work in Python, Data Science, Machine Learning, and Deep Learning
💞️ I have been working in the latest ML developments: LLMs, causal inference, explainable ML
📫 You can reach me on LinkedIn

Paulo Cysne's Projects

feature_engineering_bookcamp

Feature Engineering book by Sinan Ozdemir code

fine-tuning-llama-2-with-qlora-and-peft

This project enhances the LLaMA-2 model using Quantized Low-Rank Adaptation (QLoRA) and other parameter-efficient fine-tuning techniques to optimize its performance for specific NLP tasks. The improved model is demonstrated through a Streamlit application, showcasing its capabilities in real-time interactive settings.

galactic

data cleaning and curation for unstructured text

generative_ai_with_langchain

Build large language model (LLM) apps with Python, ChatGPT and other models. This is the companion repository for the book on generative AI with LangChain.

gliner

Generalist model for NER (Extract any entity types from texts)

hands-on-mlops-workshop

MLOps Hands-on Guide: From Training to Deployment and Monitoring: A day long workshop about MLOps

handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

julia_notebooks

Julia Jupyter/Colab Notebooks

kaobook

A LaTeX class for books, reports or theses based on https://github.com/kenohori/thesis and https://github.com/Tufte-LaTeX/tufte-latex.

kdd24-conformal

Code for Conformal Counterfactual Inference under Hidden Confounding (KDD’24)

keras-image-helper

A lightweight library for pre-processing images for pre-trained keras models

kestra

Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.

kubeflow-deep-learning

Deploying a Keras model with KServe (formerly KFServing) and EKS

kubernetes-deep-learning

Deployng a Keras model with TF-Serving and EKS

langchain

🦜🔗 Build context-aware reasoning applications

lightning-thunder

Source to source compiler for PyTorch. It makes PyTorch programs faster on single accelerators and distributed.

litgpt

Hackable implementation of state-of-the-art open-source LLMs based on nanoGPT. Supports flash attention, 4-bit and 8-bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.

llama3-from-scratch

llama3 implementation one matrix multiplication at a time

llama_parse

Parse files for optimal RAG

llm-finetuning

LLM Finetuning with peft

llm-prompt-engineering-simplified-book

LLM Prompting Engineering Simplified Book

llm.c

LLM training in simple, raw C/CUDA

llm101n

LLM101n: Let's build a Storyteller

llmlingua

To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.

llms-from-scratch

Implementing a ChatGPT-like LLM from scratch, step by step

llms-in-finance

LLMs in Finance - Generative AI - AI Agents

longrag

Official repo for "LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMs".

looper

A resource list for causality in statistics, data science and physics

machine-learning-based-loan-default-early-warning-system

Developed an end-to-end ML system on Azure to predict loan defaults, leveraging advanced data preprocessing, feature engineering, and machine learning models to optimize accuracy. This project includes a comprehensive suite of tools and techniques for robust financial risk assessment, deployed to enhance decision-making for high-risk exposures.

machine-learning-yearning

Machine Learning Yearning book by 🅰️𝓷𝓭𝓻𝓮𝔀 🆖

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