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amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

awesome-twitter-data

A list of Twitter datasets and related resources.

bertweet

BERTweet: A pre-trained language model for English Tweets (EMNLP-2020)

coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

covid-19-data

Data on COVID-19 (coronavirus) cases, deaths, hospitalizations, tests • All countries • Updated daily by Our World in Data

emulatedquestionnaireontwitter

got_network_viz_python

Exploring different options to visualize network data in Python (here Game of Thrones network)

isa616project

m3inference

A deep learning system for demographic inference (gender, age, and individual/person) that was trained on massive Twitter dataset using profile images, screen names, names, and biographies

pybaseball

Pull current and historical baseball statistics using Python (Statcast, Baseball Reference, FanGraphs)

stock-fundamental-data-scraping-and-analysis

Project on building a web crawler to collect the fundamentals of the stock and review their performance in one go

twitter-emotion-recognition

Models for predicting emotions from English tweets.

twitter-sentiment-analysis

Sentiment analysis on tweets using Naive Bayes, SVM, CNN, LSTM, etc.

vadersentiment

VADER Sentiment Analysis. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.