sohomghosh Goto Github PK

d3js

Experiments with D3.js

d3plot_from_flaskapi_or_ipythonnoebook

data-science-for-search

My notebooks for the eBay / CSUMB Data Science for Search Course

data_visualization_fdp

datasciencer

a curated list of R tutorials for Data Science, NLP and Machine Learning

deep-finance

Datasets, papers and books on AI & Finance.

deep-learning-based-sentiment-analysis-on-movie-reviews-using-word2vec

deep-learning-with-tensorflow

Deep Learning with TensorFlow by Packt

deeplearning_materials_codes_readinglist

Deep Learning codes will be added here

deploying-machine-learning-models

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

docker-demo

earningscall_dataset

The earnings conference call dataset of S&P 500 companies

ectsum

ECTSum Dataset and Codes

entity-recognition-datasets

A collection of corpora for named entity recognition (NER) and entity recognition tasks. These annotated datasets cover a variety of languages, domains and entity types.

es-swapi-test

An IPython Notebook to try Elasticsearch-py

evaluating-impact-of-social-media-posts-by-executives-on-stock-price

finance-finnum

Numeral is the crucial part of financial documents. In order to understand the detail of opinions in financial documents, we should not only analyze the text, but also need to assay the numeric information in depth. Because of the informal writing style, analyzing social media data is more challenging than analyzing news and official documents. FinNum is a dataset for fine-grained numeral understanding in financial social media data - to identify the category of a numeral.

finance-finprolex

FinProLex provides 5,162 tokens in professional analysts' reports and the financial social media platform posts with expert-like scores. The expert-like scores are calculated based on the pointwise mutual information (PMI).

finance-ntusd-fin

NTUSD-Fin provides various scoring methods including frequency, CFIDF, chi-squared value, market sentiment score and word vector for the tokens. Only the tokens appeared at least ten times and shown significantly difference between expected and observed frequency with chi-squared test are remained in our dictionary. The predetermined significance level is 0.05. The market sentiment score is calculated by substracting the bearish PMI from the bullish PMI. There are 8,331 words, 112 hashtags and 115 emojis in the constructed dictionary, NTUSD-Fin.

finance-numeracy-600k

Numeral is the crucial part of in narrative, especially in financial documents. We should not only analyze the text, but also need to assay the numeric information in depth. Numeracy-600K is a dataset for testing the numeracy of machines.

financial_narrative_summarization_2022

Solution developed by team LIPI while participating in the FNS 2022 shared task.

fincat_financial_numeral_claim_analysis_tool

A tool to detect whether numerals present in Financial Texts are in-claim or out-of-claim

fincausal-2020_2022

finclass-uai

Code for FinCLASS: Modeling Financial Uncertainty with Multivariate Temporal Entropy-based Curriculums at UAI 2021

finnlp-progress

NLP progress in Fintech. A repository to track the progress in Natural Language Processing (NLP) related to the domain of Finance, including the datasets, papers, and current state-of-the-art results for the most popular tasks.

finrad_financial_readability_assessment_dataset

FinRAD: Financial Readability Assessment Dataset - 13,000+ Definitions of Financial Terms for Measuring Readability

finsim4_esg

flask_process_from_html_form

free-data-science-books

Free resources for learning data science

getting-started-with-tensorflow

Getting Started with TensorFlow, published by Packt