Mastering Machine Learning on AWS
Dr. Saket S.R. Mengle Maximo Gurmendez
41人在讀
35.3萬字總字數
¥62.12定價
Dr. Saket S.R. Mengle Maximo Gurmendez
AWS is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud.As you go through the chapters, you’ll gain insights into how these algorithms can be trained, tuned and deployed in AWS using Apache Spark on Elastic Map Reduce (EMR), SageMaker, and TensorFlow. While you focus on algorithms such as XGBoost, linear models, factorization machines, and deep nets, the book will also provide you with an overview of AWS as well as detailed practical applications that will help you solve real-world problems. Every practical application includes a series of companion notebooks with all the necessary code to run on AWS. In the next few chapters, you will learn to use SageMaker and EMR Notebooks to perform a range of tasks, right from smart analytics, and predictive modeling, through to sentiment analysis. By the end of this book, you will be equipped with the skills you need to effectively handle machine learning projects and implement and evaluate algorithms on AWS.
the models that are trained on aws can be further optimized to run smoothly in production environments
首先看了這技術棧，亮點除了自動化了基礎設施擴展以外，真的沒啥亮點，拼算法你用的是sklearn和tf的包，拼ui你用的是jupyter，拼並行計算你用的是spark說說你的亮點在哪裏吧？ 然後再看這大局觀，MLOps時代，連給機器學習自動化和模型生命週期管理水平分級都不做，再看看對面的gcp的博文，能比麼？簡直就是研究院和地產商對科學過程抽象的區別，真的是無力吐槽，你好歹說明一下優秀的MLOps能夠自動化模型週期管理到什麼水平吧 最後再看看這書的排版，這是給人看的書麼？！代碼段練換行都不換的，這是把人當作人工智能連stopwords都去掉了讓你讀是吧？