π‘ Critical factors for enterprise data science
π‘ Advancements in supervised learning
π‘ Innovative feature engineering techniques that can significantly impact model performance?
π‘ Effectiveness of PCA versus t-SNE for visualizing high-dimensional data
π‘ How are semi and self-supervised learning approaches revolutionizing the way we train machine learning models?
π‘ Designing a scalable Machine Learning architecture
π‘ Explaining cloud-native machine learning apps
π‘ Discussing fairness and bias in Machine Learning
π‘ Securing Machine Learning applications