Practical Weak Supervision

Unlock the potential of machine learning with Practical Weak Supervision by Wee-Hyong Tok, published by O'Reilly Media in 2021. This insightful paperback, spanning 200 pages, addresses a common challenge faced by data scientists and engineers: the reliance on high-quality labeled data for training models. Manual labeling can be a tedious and costly process, but this book presents a more efficient solution. Discover how to leverage weakly supervised learning models to create innovative products without the burden of extensive labeled datasets. Join Wee-Hyong Tok, along with co-authors Amit Bahree and Senja Filipi, as they guide you through practical techniques and strategies that can enhance your machine learning projects. Perfect for professionals looking to streamline their workflow and improve model performance, this book is an essential addition to your data science library.