Название: Machine Learning Contests: A Guidebook
Автор: Wang He, Peng Liu, Qian Qian
Издательство: Springer/Posts & Telecom Press
Год: 2023
Страниц: 398
Язык: английский
Формат: pdf (true), epub
Размер: 36.8 MB
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. This book is a systematic introduction to contests in the field of algorithms, not only explaining the theory behind the practice, but also elaborating in detail the guide to scoring and necessary skills needed from various angles, using different cases. Many Deep Learning algorithms have been applying to Natural Language Processing (NLP). The early word embedding model and the subsequent development of convolutional neural networks and recurrent neural networks have played a very important role for this time period, greatly improving the accuracy baseline of the original statistical method and achieving more generalized effects in different fields (such as translation, voice recognition, and other tasks). In the current latest environment, the self-attention mechanism models like transformer structures are applicable to a sea of data, which could then generate training models.
