Learn how to automate stock and cryptocurrency research using Python and deep learning in this comprehensive tutorial video. Discover techniques for web scraping financial news, summarizing articles with natural language processing, and calculating sentiment for assets like Tesla, Bitcoin, and GameStop. Master the process of building a news and sentiment pipeline, from installing dependencies to exporting results as CSV files. Gain practical skills in using libraries such as BeautifulSoup and Hugging Face Transformers for text processing and sentiment analysis. By the end of this project-based lesson, apply the knowledge to analyze various stocks and cryptocurrencies, streamlining your financial research process.
Automate Stocks and Crypto Research with Python and Deep Learning - Full Python Project
Overview
Syllabus
​ - Start
- Explainer
- Install and Import Baseline Dependencies
- Setup Summarization Model
- Auto Summarize a Single Article
- Scrape a Single Article from Yahoo Finance
- Cleaning Scraped Data using Text Processing
- Summarize a Single Article using Hugging Face Transformers
- Building a News and Sentiment Pipeline for TSLA, BTC and GME
- Search for Stock News URLs using Google and Yahoo Finance
- Process and strip out unwanted URLs
- Scrape Cleaned Financial News Articles
- Summarize the News Pipeline
- Calculate Sentiment
- Export Results to CSV
- Running the Pipeline as a Script
- Running the Pipeline for Different Stocks and Cryptocurrencies
Taught by
Nicholas Renotte
