Name: Eason Meng
Type: User
Company: University of California Los Angeles (UCLA)
Bio: I'm a PhD candidate in Bioengineering department at UCLA. Research in machine learning for healthcare, deep learning for temporal analysis, NLP.
Location: Los Angeles, CA, USA
Blog: https://lanyexiaosa.github.io
Eason Meng's Projects
Source code for AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration
A curated list of Machine Learning and Deep Learning tutorials in Jupyter Notebook format ready to run in Google Colaboratory
Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
python code for BRLTM model
Code for - ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context (AAAI-2020)
Machine learning-Stanford University
Forte is a flexible and powerful NLP pipeline FOR TExt.
python code for HCET model
Implementation of Bayesian Hyperparameter Optimization of Machine Learning Algorithms
Public repository for multilabel classification of medical diagnoses with LSTM RNNs
My personal portfolio
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
Python code for common Machine Learning Algorithms
MiME Repository
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。
Models and examples built with TensorFlow
The code for the models described in "Learning Tasks for Multitask Learning: Heterogenous Patient Populations in the ICU" (KDD 2018).
Automatically exported from code.google.com/p/negex
:octopus: Guides, papers, lecture, and resources for prompt engineering
Simple RNN (Gated Recurrent Units) for predicting a diagnosis
TapNet: Multivariate Time Series Classification withAttentional Prototypical Network
Toolkit for Machine Learning, Natural Language Processing, and Text Generation, in TensorFlow
🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.
Python interface to Google word2vec
Complete YOLO v3 TensorFlow implementation. Support training on your own dataset.