Forecasting NFT Trade Performance

• Worked with an Australian startup to develop and implement machine learning models for predicting future prices of NFTs.

• Achieved 10% ROI on a modest NFT portfolio, validating the accuracy of predictions generated by our machine learning models.

• Engineered a robust data pipeline using Spark, collecting and preprocessing data from diverse sources like blockchain, Parsec API, OpenSea API, and social media.

• Applied advanced NLP techniques, including lemmatization, stopwords removal, and sentiment analysis (using TextBlob, Spacy, and BERT) for handling social media data.

• Implemented diverse ML models such as Random Forest, Gradient Boosting, and AutoML for accurate predictions.

• Conducted comprehensive feature engineering and selection to enhance model performance and interpretability.

• Deployed the results from the model into a nice dashboard created using Tableau for easy viewing and understanding by the stakeholders.