Rohan's Bytes

ML Case-study Interview Question: Scaling Real-Time Recommendations for Millions with Distributed Machine Learning

ML Case-study Interview Question: ML-Powered Contact Accuracy Score: Unifying Email and Company Verification

ML Case-study Interview Question: Dual Contrastive Embeddings for Balanced Two-Sided Marketplace Recommendations.

ML Case-study Interview Question: Building a Scalable Video Moderation Pipeline with Deep Learning and Human Review

ML Case-study Interview Question: XGBoost Ranking for Hybrid Recommendations: Combining Content & Collaborative Signals at Scale

ML Case-study Interview Question: Universal & Zero-Shot Models for Unified Semantic Embeddings of Reviews, Photos & Businesses.

ML Case-study Interview Question: Real-Time Harmful Text Detection in User Reviews Using LLM Classification

ML Case-study Interview Question: LLM-Powered Real-Time Scam Detection for Livestream Marketplace Messaging

ML Case-study Interview Question: Fixing E-commerce Search Queries with Language Model Expansion & Rectification

ML Case-study Interview Question: Building an LLM-Powered AI Assistant for E-commerce Sales Agent Support

ML Case-study Interview Question: Precise Ad Targeting: Uplift Decision Trees for Incremental Conversion Lift

ML Case-study Interview Question: Ranking Visually Compatible Furniture Using Deep Embeddings and Triplet Loss.