Mastering Machine Learning on AWS
Dr. Saket S.R. Mengle Maximo Gurmendez
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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
首先看了这技术栈，亮点除了自动化了基础设施扩展以外，真的没啥亮点，拼算法你用的是sklearn和tf的包，拼ui你用的是jupyter，拼并行计算你用的是spark说说你的亮点在哪里吧？ 然后再看这大局观，MLOps时代，连给机器学习自动化和模型生命周期管理水平分级都不做，再看看对面的gcp的博文，能比么？简直就是研究院和地产商对科学过程抽象的区别，真的是无力吐槽，你好歹说明一下优秀的MLOps能够自动化模型周期管理到什么水平吧 最后再看看这书的排版，这是给人看的书么？！代码段练换行都不换的，这是把人当作人工智能连stopwords都去掉了让你读是吧？