Name: Amir yazdavar
Type: User
Company: Peerlogic
Bio: Ph.D. CS, Principal Data Scientist, Former Researcher at KSU, and visiting Research at Weill Cornell, Cornell. Data science, Deep/machine Learning. NLP,
Location: Scottsdale
Blog: https://www.linkedin.com/feed/
Amir yazdavar's Projects
Code and data for the AAAI 2015 paper entitled: "Predicting the demographics of Twitter users from social evidence using website traffic data"
📚 Papers & articles of companies sharing their work on applied data science & machine learning.
Curated list of awesome papers for electronic health records(EHR) mining, machine learning, and deep learning.
Code for Biterm Topic Model (published in WWW 2013)
Code for AMIA CRI 2016 paper "Learning Low-Dimensional Representations of Medical Concepts" (http://cs.nyu.edu/~dsontag/papers/ChoiChiuSontag_AMIA_CRI16.pdf)
Notebooks and code for the book "Introduction to Machine Learning with Python"
Must-read papers on knowledge representation learning (KRL) / knowledge embedding (KE)
Minimum Viable Study Plan for Machine Learning Interviews from FAAG, Snapchat, LinkedIn.
✍️ A carefully curated list of NLP paper summaries
Palmetto is a quality measuring tool for topics
Parallel Semi-Supervised Latent Dirichlet Allocation
Simple examples to introduce PyTorch
Build your neural network easy and fast
A full spaCy pipeline and models for scientific/biomedical documents.
Detect depression on social media using the ssToT method introduced in our ASONAM 2017 paper titled "Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media"
Computation of the semantic interpretability of topics produced by topic models.