Mercury010

Mercury010

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Twitter:@TomarasT

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Mercury010's repositories

machine-learning-from-scratch

This repository contains the implementation from scratch of some of the most used Machine Learning algorithms

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ChatGPT_Trading_Bot

This is the code for the "ChatGPT Trading Bot" Video by Siraj Raval on Youtube

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pnl

FIFO PnL trading calculator in Python

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d6tstack

Quickly ingest messy CSV and XLS files. Export to clean pandas, SQL, parquet

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sec-edgar-downloader

📈 Download filings from the SEC EDGAR database using Python

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sec-edgar

Download all companies periodic reports, filings and forms from EDGAR database.

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algorithmic-trading-python

The repository for freeCodeCamp's YouTube course, Algorithmic Trading in Python

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bitcoinbook

Mastering Bitcoin 2nd Edition - Programming the Open Blockchain

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Follow-the-Big-Money-13f-files-SEC-USA

Our goal is to provide a simple tool to simplify the investment decision process for anybody. The tool helps replicate the portfolios of the most attractive stocks in the capital markets without paying any management fees.

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ML-For-Beginners

12 weeks, 24 lessons, classic Machine Learning for all

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Mercury010

Config files for my GitHub profile.

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blockchain-demo

A web-based demonstration of blockchain concepts.

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py

Repository to store sample python programs for python learning

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best-of-ml-python

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

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csvtotable

Simple command-line utility to convert CSV files to searchable and sortable HTML table.

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TIA

Your Advanced Twitter stalking tool

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Real-time-Sentiment-Tracking-on-Twitter-for-Brand-Improvement-and-Trend-Recognition

A real-time interactive web app based on data pipelines using streaming Twitter data, automated sentiment analysis, and MySQL&PostgreSQL database (Deployed on Heroku)

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trading-pnl

FIFO Trading Model for PnL Calculation

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stock-visualizer

A Python application that visualizes stock data using professional candlestick charts.

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Twitter-moods-as-stock-price-predictors-on-Nasdaq

An attempt to predict next day's stock price movements using sentiments in tweets with cashtags. Six different ML algorithms were deployed (LogReg, KNN, SVM etc.). Main libraries used: Pandas & Numpy

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