Goldman Sachs ML Sentiment Analysis
Applied NewsAPI for web scraping to compute relevant stock sentiment primarily through Bloomberg, CNN, Business Insider, Financial Times, and Reuters. Used Twitter API for real-time posts relating to the stock embedded into the app. This is a trending topic in Event-Driven Investing, used by many quant firms and hedge funds.
Used a Long-Short-Term-Memory Recurrent Neural Network (LSTM-RNN) Model that could track temporal changes of stock price, growth score, financial return score, multiple score, and integrated score with a 50-day moving average, which is a commonly used technical indicator for short-term price movement. Trained the neural network on Google Cloud Services and NVIDIA Tesla P100 GPU.
Developed a web application using Bootstrap that uses a custom search bar to query historical stock trade data from a MySQL database. The plan was to utilize the data to provide trends and graphs.
Thank you @lilianweng for the TensorFlow base model
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