emmyphung's Projects
Using data about 911 calls in the US, this project gives insights about regions having the most incidents, frequencies of calls, reasons of calls, and prediction of number of calls in the coming years.
This project will explore the Airbnb market in NYC
A curated list of awesome Machine Learning frameworks, libraries and software.
Review employees' review about big tech companies.
BMSC-GA 4493 Deep Learning in Medicine - Spring 2020
This notebook provides a replicate of my work as a research assistant at Trinity College. I'll leave out the data cleansing part which I did for a first couple of months and only focus on the modelling here. You can check the data cleansing and EDA in the EDA notebooks.
The goal of this project is to predict the infection rate of these missing counties based on their county feature data, including but not limited to population, education, public and private healthcare information, and popular transportation methods
Python for Harvesting Data on the Web
This holds iPython notebooks and lecture slides for the Intro to Data Science Master's course I teach at NYU.
A file pages counter
Machine Learning (DS-GA 1003)
DS-GA 1003: Machine Learning
I will save all my writings and blogging for DSinbrief here.
Portfolio
PyTorch code for end-to-end spoken language understanding (SLU) with ASR-based transfer learning
A quick reference to access NYU High Performance Computing
Implementation of Bayesian Hyperparameter Optimization of Machine Learning Algorithms
This repo will house all our course material and code snippets from the Introduction to Machine Learning Class
Kaggle Competition. URL: https://www.kaggle.com/c/google-quest-challenge/overview
Example of Matrix Multiplication using Map Reduce paradigm in python
Minimal is a Jekyll theme for GitHub Pages
Portfolio
In this self-study project, I will build a movie recommender system based on users' ratings.
The project aims at tracking the three phase transformation of neuroendocrine cells specific to the human colon, which is illustrated in the figure below. A stem cell transforms into a progenitor cell and finally a mature cell through symmetric and asymmetric cell division. Symmetric cell division, also known as self-renewal, occurs when a stem cell divides symmetrically into two identical stem cells. Asymmetric cell division characterizes the maturation process when a stem cell divides into a stem cell and a progenitor cell, or a progenitor cell divides into a progenitor cell and a mature cell. In each phase, cells also experience apoptosis. meaning cell death. With an aim to capture this phenomenon, I want to build a model that track the number of cells in each phase, stem cells, progenitor cells and mature cells.
Jupyter Notebooks from the old UnsupervisedLearning.com (RIP) machine learning and statistics blog
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