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Learn to craft GPT-3 prompts for extracting, classifying, and structuring information from financial text.
Build a voice assistant with Python, Gradio, Whisper speech-to-text, and ChatGPT that responds through your computer’s audio.
Explore a full-stack web application using Interactive Brokers Web API. Learn about dashboard, portfolio, market data, order submission, and market scanner functionalities through detailed code walkthroughs.
Explore how to use Gemini API to extract and analyze financial predictions from YouTube videos, using Python and Yahoo Finance data to evaluate their accuracy over time.
Master implementing intraday Opening Range Breakout strategies using Backtesting.py with position sizing, stop losses, and performance analysis for algorithmic trading.
Discover how to backtest trading strategies using Python's backtesting.py library in this practical 10-minute tutorial with code examples.
Master opening range breakout trading strategy implementation using Python, ib_async library, and Interactive Brokers API with real-time monitoring and automated order placement.
Explore Perplexity AI's financial tools including SEC API access, watchlists, earnings transcripts, natural language stock screening, and crypto analysis for investment research.
Master building a full-stack trading dashboard by integrating Interactive Brokers API with TradingView charts, FastAPI backend, and real-time market data streaming capabilities.
Discover how to build a web-based market scanner using Interactive Brokers API with frontend templates, JavaScript integration, and real-time data visualization features.
Master real-time streaming data with Interactive Brokers API using Server-Sent Events, JavaScript EventSource, and browser integration for live market data visualization.
Explore Kalshi API integration with Python to analyze Super Bowl prop betting data and automate order placement using programmatic trading strategies.
Discover how to build a Python trading bot for Kalshi NFL prediction markets, exploring API integration, real-time data processing, and the challenges of latency in automated trading.
Uncover why prediction market bettors consistently lose money through analysis of 72 million Kalshi trades, exploring biases, market microstructure, and winning strategies.
Master asynchronous programming with Interactive Brokers API using Python's ib_async library to efficiently fetch historical data for multiple symbols simultaneously.
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