Based on the Judicial Transparency Index Assessment (2019 and 2020) conducted in China by the Institute of Law of the Chinese Academy of Social Sciences, this book summarizes and analyzes the current situation of judicial openness in China, using a sample of 218 courts across the country for the study. The book analyzes the ideological and institutional origins of judicial openness and examines the operation of judicial openness through the practical experience of role replacement. By analyzing evaluation data in the fields of audit information disclosure, trial information disclosure, judicial enforcement data disclosure, and judicial reform data disclosure, the book points out that the current judicial disclosure has made significant progress, but there are still problems such as unclear disclosure standards, insufficient rigidity in disclosure requirements, and the scope of disclosure still needs to be expanded. The book recommends accelerating the disclosure of judicial legislation, public standards, and strengthening assessment and accountability.

This book systematically introduces the competitions in the field of algorithm and machine learning. The first author of the book has won 5 championships and 5 runner-ups in domestic and international algorithm competitions.Firstly, it takes common competition scenarios as a guide by giving the main processes of using machine learning to solve real-world problems, namely problem modelling, data exploration, feature engineering, model training. And then lists the main points of difficulties, general ideas with solutions in the whole process. Moreover, this book comprehensively covers several common problems in the field of machine learning competitions such as recommendation, temporal prediction, advertising, text computing, etc. The authors, also knew as "competition professionals”, will explain the actual cases in detail and teach you various processes, routines, techniques and strategies, which is a rare treasure book for all competition enthusiasts. It is very suitable for readers who are interested in algorithm competitions and deep learning algorithms in practice, or computer-related majors.