11 skills found
lmammino / FinancialA Zero-dependency TypeScript/JavaScript financial library (based on numpy-financial) for Node.js, Deno and the browser
numpy / Numpy FinancialStandalone package of the NumPy financial functions
razorpay / Go FinancialA go port of numpy-financial functions and more.
orcaman / Financialthink numpy's financial (npv, irr, etc.) but in go
mpquant / Python Financial Technical Indicators PandasTechnical Indicators implemented in Python only using Numpy-Pandas as Magic - Very Very Fast! Very tiny! Stock Market Financial Technical Analysis Python library . Quant Trading automation or cryptocoin exchange
ntrang086 / Analyze Financial Dataanalyze financial data using python: numpy, pandas, etc.
wowinter13 / Finance RbA ruby port of numpy-financial functions and more.
mjmacarty / Numpy FinancialNo description available
tk3369 / NPFinancial.jlNPFinancial.jl is a port of the NumPy's financial module
RaghavsScarletSplendour / MonteCarloSimStockPricesThis project explores the application of Monte Carlo simulation techniques to predict stock price movements over time. Utilizing Python and libraries such as NumPy and Matplotlib, it offers a hands-on approach to understanding the stochastic nature of financial markets and the practical application of statistical methods in finance.
AYSE-DUMAN / Sentiment Analysis On Stocks Data Using NLPThis study is about creating a sensitivity classifier model using messages from customers. We have a binary classification problem that categorizes stock sensitivity data as positive or negative. 1 indicates positive sentiment and 0 indicates negative sentiment. The main resource I used in the study is the Python & Machine Learning for Financial Analysis course on Udemy. The main steps are as follows: Importing required libraries(pandas,numpy,seaborn,matplotlib,nltk,gensim,tensorflow) Explanatory Data Analysis Data cleaning (removing punctuations and stopwords from text) Visualization of cleaned dataset and plotting wordcloud Prepare the data by tokenizing and padding Building a custom-based deep neural network for sentiment analysis (embedding layer, LSTM network) Making prediction and assessing the model performance (confusion matrix)
