prabhakar-g,github

ai-for-finance-stocks-real-time-analysis-

• First we fetch data of stocks in realtime from nse India website, perform basis data visualizations using python to analyze the stock. • Then we use machine learning LSTM technique to predict the future stock price and at last create an interactive web-app using Streamlit in python.

aialpha

Use unsupervised and supervised learning to predict stocks

aws-bookstore-demo-app

AWS Bookstore Demo App is a full-stack sample web application that creates a storefront (and backend) for customers to shop for fictitious books. The entire application can be created with a single template. Built on AWS Full-Stack Template.

bhavcopy-downloader

Get free NSE and BSE data(bhavcopy), based on customizable index and date. Give it a star if you like it

bsedata

Python library for extracting real-time data from Bombay Stock Exchange (India)

how-to-predict-stock-prices-easily-demo

How to Predict Stock Prices Easily - Intro to Deep Learning #7 by Siraj Raval on Youtube

machinelearningstocks

Using python and scikit-learn to make stock predictions

nifty50_index_movement_prediction

## What is Nifty National Stock Exchange Fifty or Nifty is the market indicator of NSE. It ideally is a collection of 50 stocks but presently has 51 listed in it. It is also referred to as Nifty 50 and CNX Nifty by some as it is owned and managed by India Index Services and Products Ltd. (IISL). ## How is Nifty index calculated? Nifty is also calculated through the free-float market capitalization weighted method. Just like Sensex, Nifty also follows a mathematical formula based to know the market capitalization. It multiples the Equity capital with a price to derive the market capitalization. To determine the Free-float market capitalization, equity capital is multiplied by a price which is further multiplied with IWF which is the factor for determining the number of shares available for trading freely in the market. The Index is determined on a daily basis by taking into consideration the current market value divided by base market capital and then multiplied by the Base Index Value of 1000.

nse_trader

A basic implementation to download historic prices, apply a strategy, and see the strategy performance vis-a-vis the actual stock prices.

stock-market-analysis-and-prediction

Stock Market Analysis and Prediction is the project on technical analysis, visualization and prediction using data provided by Google Finance.

stock-market-india

API for Indian Stock Market's NSE and BSE.

stock-market-prediction-and-notification-system

: To conduct a stock market analysis for National Stock Exchange ( NSE) and Bombay Stock Exchange (BSE) in India. By using LSTM algorithm for the technical, fundamental, current affairs and miscellaneous analysis for prediction purposes. These analysis will keep track of the trend of all the listed Indian companies and it will store a useful feedback as history of the working day

stock-market-prediction-using-machine-learning

• Predicting the future of stocks short term buy, sell and hold signals for companies like ONGC, SBI, ITC, HCL and etc. based on historical data from NSE using features like opening price, closing price, high low and volume.

stock-market-prediction-web-app-using-machine-learning-and-sentiment-analysis

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

stock-prediction

The git is about Indian Stock market prediction.

stock-price-prediction-lstm

OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network

stock-price-prediction-time-series-lstm-model-keras-tensorflow

This is a model that has been trained on historical data obtained from Yahoo Finance. The data set comprises of all data records starting from the launch date of this stock in India (1996). This model aims to pick up key trends in the stock price fluctuations based on Time Series mapping. It is able to render predictions for the upcoming time period. The accuracy as obtained on the training data-set is about 90 percent and it successfully demonstrates key trends. It can be simulated on any stock in the market provided their historical data is made available. (One could use the yfinance API or download manually). Keras is used extensively along with Tensorflow for training. The model features 100 epochs of Base size 64. The training time depends on the hardware being used by the user. It is advisable to be performed on Google Colaboratory. For any issues/suggestions write to [email protected]

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