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Everyday things people use in Pytorch. No need to spend hours reading Pytorch forums trying to find them!
this repo provides some earlier visualizations I had done in R.
Abstract Depression brings significant challenges to the overall global public health. Each day, millions of people suffered from depression and only a small fraction of them undergo proper treatments. In the past, doctors will diagnose a patient via a face to face session using the diagnostic criteria that determine depression such as the Depression DSM-5 Diagnostic Criteria. However, past research revealed that most patients would not seek help from doctors at the early stage of depression which results in a declination in their mental health condition. On the other hand, many people are using social media platforms to share their feelings on a daily basis. Since then, there have been many studies on using social media to predict mental and physical diseases such as studies about cardiac arrest (Bosley et al., 2013), Zika virus (Miller, Banerjee, Muppalla, Romine, & Sheth, 2017), prescription drug abuse (Coppersmith, Dredze, Harman, Hollingshead, & Mitchell, 2015) mental health (De Choudhury, Kiciman, Dredze, Coppersmith, & Kumar, 2016) and studies particularly about depressive behavior within an individual (Kiang, Anthony, Adrian, Sophie, & Siyue, 2015). This research particularly focuses on leveraging social media data for detecting depressive thoughts among social media users. In essence, this research incorporated text analysis that focuses on drawing insights from written communication in order to conclude whether a tweet is related to depressive thoughts. This research produced a web application that performs a real-time enhanced classification of tweets based on a domain-specific lexicon-based method, which utilizes an improved dictionary that consists of depressive and non-depressive words with their associated orientations to classify depressive tweets. Problem understanding or Business Understanding Depression is the main cause of disability worldwide (De Choudhury et al., 2013). Statistically, an estimation of nearly 300 million people around the world suffers from depression. Shen et al (2017) mentioned that approximately 70% of people with early stages of depression would not consult a clinical psychologist. Many people are utilizing social media sites like Facebook and Instagram to disclose their feelings. This research persists the hypothesis that there are similarities between the mental state of an individual and the sentiment of their tweets and investigated the potentiality of social media (like twitter) as a data source for classifying depression among individuals.
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
A pricing model, which can predict the acceptable per night price for Airbnb apartment based on its properties and the offered amenities
References to the Medium articles
[UNMAINTAINED] Automated machine learning for analytics & production
Automating the process of data pre-processing and model training in Machine Learning.
Autoencoder on tabular data
Set of Machine Learning and Stochastic Optimazion tools based on Hadoop, Spark and Storm https://pkghosh.wordpress.com/
:page_facing_up: Awesome CV is LaTeX template for your outstanding job application
A curated list of references for MLOps
end to end predictive modeling framework leveraging multiple ML techniques for bid pricing
Sentiment analysis (sometimes known as opinion mining or emotion AI) refers to the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.
Google AI 2018 BERT pytorch implementation
🪐 Book on Python, Algorithms, and Data Structures. 🪐
Up Your Bus Number: A Primer for Reproducible Data Science
caret (Classification And Regression Training) R package that contains misc functions for training and plotting classification and regression models
Causal Feature Selection Tutorial for AMIA2018
Code for the EACL 2021 Paper: Clinical Outcome Prediction from Admission Notes using Self-Supervised Knowledge Integration
Blog post on Medium
Fraud detection algorithm using Autoencoders and Stacked Autoencoders to detect fraudulent physicians in CMS Part B claims data
This R package calculates CMS-HCC risk scores as an alternative to using SAS
Definition and DDLs for the OMOP Common Data Model (CDM)
Code for predicting risky behavior in social communities.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.