About Me

 Manu Joseph was honored with the prestigious 40 Under 40 Data Scientist award by Analytics India Magazine (AIM), recognizing his significant contributions to the field of data science and his leadership in time series forecasting and deep learning for tabular data. 

 Manu Joseph's best-selling book, "Modern Time Series Forecasting with Python," bridges classical statistical methods and modern machine learning techniques to forecast at scale. It's a comprehensive guide for data scientists and analysts, offering industry-tested strategies and insights into global forecasting models and deep learning applications in time series. 

 PyTorch Tabular, developed by Manu, revolutionizes deep learning for tabular data by making it accessible and efficient. This open-source library facilitates the easy customization of models for real-world use cases, leveraging PyTorch's intuitive architecture and PyTorch Lightning's simplified training process. 

 "Little Pajama Tales," an AI-generated children's story podcast co-created by Manu, aims to enrich bedtime with imaginative 5-minute stories. The podcast emphasizes the importance of listening skills, imagination, family bonding, and cognitive development, reaching 1000+ downloads across 20+ countries.

 GANDALF, a novel tabular model introduced by Manu, sets new benchmarks in deep learning for tabular data with its Gated Feature Learning Unit (GFLU). It combines high performance, interpretability, and efficiency, challenging state-of-the-art models like XGBoost and FT-Transformers in public benchmarks, and is available under the MIT License. 

 In his roles across various organizations, Manu has spearheaded projects in time series forecasting, predictive quality, recommendation systems, and marketing mix modeling using machine learning. His unpublished, proprietary work continues to push the boundaries of AI and machine learning in business applications.