03368nam a22004335i 4500 ssj0002240198 WaSeSS 20220419114800.0 m d cr n 190907s2019 xxu| o |||| 0|eng d 9781484248584 WaSeSS AIMIT LIBRARY QA76.73.P98 UMX bicssc COM051360 bisacsh UMX thema 005.76 1 VARE EBOOK Varga, Ervin 30379 Practical Data Science with Python 3 : synthesizing actionable insights from Data / By Ervin Varga. 1st ed. Berkeley : Apress : 2019. Xvii, 462p. 23.5 cm. text file PDF rda Chapter 1.Introduction to Data Science -- Chapter 2.Data Acquisition -- Chapter 3.Basic Data Processing -- Chapter 4.Documenting Work -- Chapter 5.Transformation and Packaging of Data -- Chapter 6.Visualization -- Chapter 7.Prediction and Inference -- Chapter 8.Network Analysis -- Chapter 9.Data Science Process Engineering -- Chapter 10. Multi-agent Systems, Game Theory and Machine Learning -- Chapter 11. Probabilistic Graphical Models -- Chapter 12. Security in Data Science. Requires an SPL library card. Gain insight into essential data science skills in a holistic manner using data engineering and associated scalable computational methods. This book covers the most popular Python 3 frameworks for both local and distributed (in premise and cloud based) processing. Along the way, you will be introduced to many popular open-source frameworks, like, SciPy, scikitlearn, Numba, Apache Spark, etc. The book is structured around examples, so you will grasp core concepts via case studies and Python 3 code. As data science projects gets continuously larger and more complex, software engineering knowledge and experience is crucial to produce evolvable solutions. You'll see how to create maintainable software for data science and how to document data engineering practices. This book is a good starting point for people who want to gain practical skills to perform data science. All the code will be available in the form of IPython notebooks and Python 3 programs, which allow you to reproduce all analyses from the book and customize them for your own purpose. You'll also benefit from advanced topics like Machine Learning, Recommender Systems, and Security in Data Science. Practical Data Science with Python will empower you analyze data, formulate proper questions, and produce actionable insights, three core stages in most data science endeavors. Mode of access: World Wide Web. Estimating the edge betweenness centrality 30380 Partitioning the model into a bipartite graph 30381 Electronic books. local 30382 Springer eBooks Printed edition: 9781484248584 Printed edition: 9781484248607 View this electronic item in O'Reilly Online Learning: Academic/Public Library Edition. https://ezproxy.spl.org/login?url=https://learning.oreilly.com/library/view/~/9781484248591/?ar An e-book available through full-text database. ddc BK 1st 005.76 VARE 222479 222479 03658530 0 0 ddc 0 0 MCA AIMIT AIMIT 2022-03-24 Biblios Book Point 1299.00 Bill no:6623; Bill dt:2022-03-23 0 005.76 VARE MCA17068 2026-05-23 00:00:00 1039.20 2022-04-19 BK