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Key benefits

Create networks using data points and information

Learn to visualize and analyze networks to better understand communities

Explore the use of network data in both - supervised and unsupervised machine learning projects

Purchase of the print or Kindle book includes a free PDF eBook

Description

Network analysis is often taught with tiny or toy data sets, leaving you with a limited scope of learning and practical usage. Network Science with Python helps you extract relevant data, draw conclusions and build networks using industry-standard – practical data sets. You’ll begin by learning the basics of natural language processing, network science, and social network analysis, then move on to programmatically building and analyzing networks. You’ll get a hands-on understanding of the data source, data extraction, interaction with it, and drawing insights from it. This is a hands-on book with theory grounding, specific technical, and mathematical details for future reference. As you progress, you’ll learn to construct and clean networks, conduct network analysis, egocentric network analysis, community detection, and use network data with machine learning. You’ll also explore network analysis concepts, from basics to an advanced level. By the end of the book, you’ll be able to identify network data and use it to extract unconventional insights to comprehend the complex world around you.

Who is this book for?

Network Science with Python demonstrates how programming and social science can be combined to find new insights. Data scientists, NLP engineers, software engineers, social scientists, and data science students will find this book useful. An intermediate level of Python programming is a prerequisite. Readers from both – social science and programming backgrounds will find a new perspective and add a feather to their hat.

What you will learn

Explore NLP, network science, and social network analysis

Apply the tech stack used for NLP, network science, and analysis

Extract insights from NLP and network data

Generate personalized NLP and network projects

Authenticate and scrape tweets, connections, the web, and data streams

Discover the use of network data in machine learning projects

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Colour book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

$38.99

Interpretable Machine Learning with Python

$38.99

Causal Inference and Discovery in Python

$40.99

Total $ 118.97

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Shipments are not trackable

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Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

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Amazon verified reviews

Kindle Customer Dec 04, 2023

I learned all about graphs and networks in College a few decades ago. It has proven fairly useless knowledge to me.This book, on the other hand, is incredible. I can now see how these tools and approaches are relevant to my work in data. It's really reshaped how I think of data problems through brilliant examples and with appropriate context.David has taken the Academic and made it Useful. And it's wicked cool!

Amazon Verified review

Om S Mar 12, 2023

The book "Network Science with Python" is an excellent resource for anyone looking to learn how to create networks using data points and information. The author provides a hands-on approach to learning about network science, natural language processing, and social network analysis.The book is well-organized, with a clear and concise table of contents that makes it easy to navigate. The first few chapters introduce the basics of natural language processing and network science, followed by useful Python libraries for these topics. The author then demonstrates how to extract insights from NLP and network data, and generate personalized NLP and network projects.One of the standout features of this book is its emphasis on practical applications of network analysis. The author includes detailed instructions on how to authenticate and scrape tweets, connections, the web, and data streams. Readers will learn how to construct and clean networks, conduct egocentric network analysis, and detect communities within networks.The final chapters of the book explore the use of network data in both supervised and unsupervised machine learning projects. The author provides detailed explanations of these concepts, making them accessible to readers from both social science and programming backgrounds.Overall, "Network Science with Python" is a valuable resource for anyone interested in learning about network analysis and its practical applications. The inclusion of specific technical and mathematical details ensures that readers will have a solid foundation for future reference. The purchase of the print or Kindle book also includes a free PDF eBook, making it a great value for anyone looking to expand their knowledge of network science.

zuluwhiskey May 17, 2023

As a data scientist, NLP is an area I've had limited experience in. It was never as striking to me as other areas of data science. But I've followed David Knickerbocker for a while now and was happy to purchase this the moment I saw his announcement on LinkedIn. It is hard for me to imagine a better introduction to this topic and it was, I think, precisely what I needed. The linear progression and friendly tone makes it highly bingeable. It is written with contagious enthusiasm and seasoned wisdom. It quite plainly communicates the profundity and power of a good network analysis - and this is what I never understood, why I should ever care, what all can really be done with a graph? David answers by providing quickly digestible examples and inspires a curiosity to explore. This is a hit-the-ground-running book, a why-should-I-care-answer book, and a I-didn't-know-I'd-find-this-so-interesting book. Needless to say, I look forward to exploring these concepts with my own projects. David's enthusiasm is indeed contagious.

Ben Bearden Mar 21, 2023

I've had an awesome time reading and applying the concepts of David Knickerbocker's book "Network Science with Python" to my own research.Above is a social network of Russian propaganda channels on Telegram that I've made using the techniques he laid out in his book.It is still a work in progress, but I am baffled by the applicability of network science to OSINT and research in general.Still reading but am thoroughly enjoying it thus far!

Gerald H. SHUDY Jr. May 10, 2023

Having followed David on LinkedIn for some time and getting advice from him occasionally, I was very excited to get the “collected wisdom” of his journey in an easy-to follow and FUN book!It’s everything I hoped for and even though I’m not finished yet, I had to come here to say this. :-)

Network Science with Python: Explore the networks around us using network science, social network analysis, and machine learning

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