Data Science at Scale with Python and Dask - Jesse Daniel
-25% su kodu BOOKS
Pristatymas per 31-37 d.d.
30 dienų grąžinimo politika
Large datasets tend to be distributed, non-uniform, and prone to change. Dask simplifies the process of ingesting, filtering, and transforming data, reducing or eliminating the need for a heavyweight framework like Spark. Data Science at Scale with Python and Dask teaches readers how to build distributed data projects that can handle huge amounts of data. The book introduces Dask Data Frames and teaches hel ... Visas aprašymas
Jums taip pat gali patikti
Aprašymas
Large datasets tend to be distributed, non-uniform, and prone to change. Dask simplifies the process of ingesting, filtering, and transforming data, reducing or eliminating the need for a heavyweight framework like Spark.
Data Science at Scale with Python and Dask teaches readers how to build distributed data projects that can handle huge amounts of data. The book introduces Dask Data Frames and teaches helpful code patterns to streamline the reader's analysis.
Key Features
- Working with large structured datasets
- Writing DataFrames
- Cleaningand visualizing DataFrames
- Machine learning with Dask-ML
- Working with Bags and Arrays
Written for data engineers and scientists with experience using Python. Knowledge of the PyData stack (Pandas, NumPy, and Scikit-learn) will be helpful. No experience with low-level parallelism is required.
About the technology
Dask is a self-contained, easily extendible library designed to query, stream, filter, and consolidate huge datasets.
Jesse Daniel has five years of experience writing applications in Python, including three years working with in the PyData stack (Pandas, NumPy, SciPy, Scikit-Learn). Jesse joined the faculty of the University of Denver in 2016 as an adjunct professor of business information and analytics, where he currently teaches a Python for Data Science course.
Daugiau informacijos
| Autorius | Jesse Daniel |
|---|---|
| Leidėjas | Manning Publications |
| Išleidimo metai | 2019 |
| Viršelio tipas | Minkšti viršeliai |
| EAN | 9781617295607 |