- Main
- Computers - Organization and Data Processing
- Fast Python for Data Science (MEAP V8)
Fast Python for Data Science (MEAP V8)
Tiago Rodrigues Antao你有多喜欢这本书?
下载文件的质量如何?
下载该书,以评价其质量
下载文件的质量如何?
Chapters 1 to 5, 7 to 10 of 10
Lastest book name is:
Fast Python: High performance techniques for large datasets
Master these effective techniques to reduce costs and run times, handle huge datasets, and implement complex machine learning applications efficiently in Python. Fast Python for Data Science is a hands-on guide to writing Python code that can process more data, faster, and with less resources. It takes a holistic approach to Python performance, showing you how your code, libraries, and computing architecture interact and can be optimized together. Written for experienced practitioners, Fast Python for Data Science dives right into practical solutions for improving computation and storage efficiency. You'll experiment with fun and interesting examples such as rewriting games in lower-level Cython and implementing a MapReduce framework from scratch. Finally, you'll go deep into Python GPU computing and learn how modern hardware has rehabilitated some former antipatterns and made counterintuitive ideas the most efficient way of working.
Lastest book name is:
Fast Python: High performance techniques for large datasets
Master these effective techniques to reduce costs and run times, handle huge datasets, and implement complex machine learning applications efficiently in Python. Fast Python for Data Science is a hands-on guide to writing Python code that can process more data, faster, and with less resources. It takes a holistic approach to Python performance, showing you how your code, libraries, and computing architecture interact and can be optimized together. Written for experienced practitioners, Fast Python for Data Science dives right into practical solutions for improving computation and storage efficiency. You'll experiment with fun and interesting examples such as rewriting games in lower-level Cython and implementing a MapReduce framework from scratch. Finally, you'll go deep into Python GPU computing and learn how modern hardware has rehabilitated some former antipatterns and made counterintuitive ideas the most efficient way of working.
年:
2022
出版:
MEAP Version 8
出版社:
Manning Publications
语言:
english
页:
273
ISBN 10:
1617297933
ISBN 13:
9781617297939
文件:
PDF, 23.41 MB
您的标签:
IPFS:
CID , CID Blake2b
english, 2022
在1-5分钟内,文件将被发送到您的电子邮件。
该文件将通过电报信使发送给您。 您最多可能需要 1-5 分钟才能收到它。
注意:确保您已将您的帐户链接到 Z-Library Telegram 机器人。
该文件将发送到您的 Kindle 帐户。 您最多可能需要 1-5 分钟才能收到它。
请注意:您需要验证要发送到Kindle的每本书。检查您的邮箱中是否有来自亚马逊Kindle的验证电子邮件。
正在转换
转换为 失败