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followers: 30.0 following: 30.0 repos: 20.0 gists: 0.0

Name: Meng Chen

Type: User

Bio: A passionate MLE and LLM practitioner always looking for adventures in the AI space.

Blog: biomchen.github.io

Welcome to AI / GenAI Hub

Introduction

I am a Data Scientist with a PhD in Evolutionary Biology from the University of Washington, Seattle. As a data scientist, I am interested in finding business insight by implementing cutting-edge machine learning techniques and GenAI and building products in different scales to execute actionable recommendations for a variety of businesses.

🔭 I’m currently working on LLM implementaions in a variety of scales
🧠 Some GenAI-related tasks I'm working on:
- Serving LLMs with APIs
- Fine tuning embedding models (e.g., bge-large-en-1.5)
- Parameterization efficiency fine tuning Open Source LLMs (e.g., Llama-2-7b & Llama-2-13b)
- Reinforcement Learning from Human Feedback
⚡ Highlighted Projects
- One-stop ChatBot implementation using CoT, RAG, and Relational DB (NLU, GenAI)
- Knowledge Graph implementation of the RAG (GenAI)
- Complaint Loss Detector (NLP) https://github.com/biomchen/complaint_loss_detector

Skills

GitHub Stats

status

streak status

Top Languages

🖥️ You can find me at LinkedIn

Meng Chen's Projects

aws-mlops

AWS MLOps

biomchen

complaint_loss_detector

A NLP and ML powered tool for monetary loss reduction

d2l-en

Dive into Deep Learning: an interactive deep learning book with code, math, and discussions

deep-learning-book

Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"

doc-split-estimator

ds-take-home

My solution to the book A Collection of Data Science Take-Home Challenges

mammal-community

Study on Evolutionary Ecology of Mammalian Communities through Time

ml-algorithms

Personal Summary of the ML Algorithms

morphometrics-locomotion

openai-gpt-serving-api

Serve locally for integration with frontend development

raspberrypi-spark-cluster

A brief description of building a RaspberryPi-powered Spark Cluster

spark-in-docker

stat479-deep-learning-ss19

Course material for STAT 479: Deep Learning (SS 2019) course at University Wisconsin-Madison

stat479-machine-learning-fs18

Course material for STAT 479: Machine Learning (FS 2018) at University Wisconsin-Madison

takehomedatachallenges

My solution to the book <A collection of Data Science Take-home Challenges>

torch2trt

An easy to use PyTorch to TensorRT converter

vicuna-deployment

Detailed steps about how to deploy the Vicuna using fastchat.

voice-engine

building blocks to create voice interface applications

whisper

Robust Speech Recognition via Large-Scale Weak Supervision

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