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Author
Publisher
O'Reilly Media, Inc
Language
English
Formats
Description
"Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create...
Author
Language
English
Formats
Description
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the...
Author
Publisher
Morgan Kaufmann
Pub. Date
[2017]
Language
English
Description
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating...
Author
Publisher
O'Reilly Media, Inc
Pub. Date
2021
Language
English
Description
Data analytics may seem daunting, but if you're familiar with Excel, you have a head start that can help you make the leap into analytics. Advancing into Analytics will lower your learning curve. Author George Mount, founder and CEO of Stringfest Analytics, clearly and gently guides intermediate Excel users to a solid understanding of analytics and the data stack. This book demonstrates key statistical concepts from spreadsheets and pivots your existing...
Author
Publisher
O'Reilly Media
Language
English
Appears on list
Formats
Description
Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they're also a good way to dive into the discipline without actually understanding data science. With this updated second edition, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get...
Author
Publisher
O'Reilly Media
Pub. Date
2018.
Language
English
Formats
Description
"Mine the rich data tucked away in popular social websites like Twitter, Facebook, LinkedIn, Instagram, and GitHub. With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media--who's connecting with whom, what they're talking about, and where they're located--using Python code examples, Jupyter notebooks, or Docker containers."--Back cover.
Author
Language
English
Formats
Description
Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the new edition of Python Data Science Handbook do you get them all--Python, NumPy, pandas, Matplotlib, scikit-learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python...
Author
Publisher
O'Reilly media
Pub. Date
2022.
Language
English
Description
Do your product dashboards look funky? Are your quarterly reports stale? Is the data set you're using broken or just plain wrong? These problems affect almost every team, yet they're usually addressed on an ad hoc basis and in a reactive manner. If you answered yes to these questions, this book is for you. Many data engineering teams today face the "good pipelines, bad data" problem. It doesn't matter how advanced your data infrastructure is if the...
Author
Publisher
Apress
Pub. Date
[2019]
Language
English
Description
Discover how to use the popular RStudio IDE as a professional tool that includes code refactoring support, debugging, and Git version control integration. This book gives you a tour of RStudio and shows you how it helps you do exploratory data analysis; build data visualizations with ggplot; and create custom R packages and web-based interactive visualizations with Shiny. In addition, you will cover common data analysis tasks including importing data...
Author
Publisher
MIT Sloan Management Review
Pub. Date
2018.
Language
English
Description
The successful use of analytics in sports, both on the field and off, comes down to integrating analytics within an organization. Three strategies - collaborative analytics, a common language, and accessible technology - are key.
Author
Publisher
O'Reilly Media, Inc
Pub. Date
[2023]
Language
English
Description
Today, enterprises have more data at their disposal than ever before. Yet relatively few companies can quickly and efficiently get data to the people who need it for critical insights and important decisions. In this insightful report, David Sweenor and Melissa Burroughs from Alteryx explain analytic democratization, a strategy that leading organizations are now using to manage data access, analytics platforms, and data-driven decision-making. By...
Publisher
O'Reilly
Pub. Date
2020.
Language
English
Description
Most of the high-profile cases of real or perceived unethical activity in data science aren't matters of bad intent. Rather, they occur because the ethics simply aren't thought through well enough. Being ethical takes constant diligence, and in many situations identifying the right choice can be difficult. In this in-depth book, contributors from top companies in technology, finance, and other industries share experiences and lessons learned from...
Publisher
Scrivener Publishing
Pub. Date
2022
Language
English
Description
Data, the latest currency of today's world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate...
Author
Publisher
Packt Publishing, Limited
Pub. Date
2022
Language
English
Description
Create scalable and reliable data pipelines easily with Pachyderm Key Features Learn how to build an enterprise-level reproducible data science platform with Pachyderm Deploy Pachyderm on cloud platforms such as AWS EKS, Google Kubernetes Engine, and Microsoft Azure Kubernetes Service Integrate Pachyderm with other data science tools, such as Pachyderm Notebooks Book Description Pachyderm is an open source project that enables data scientists to run...
Author
Publisher
Dpunkt.verlag
Pub. Date
2022
Language
Deutsch
Description
Dieses Buch bietet einen praxisnahen Einstieg in Data Science, angereichert mit interaktiven Elementen, der die Breite der M�glichkeiten der Datenanalyse aufzeigt und tief genug geht, um Vorteile, Nachteile und Risiken zu verstehen, aber dennoch nicht zu tief in die zugrunde liegende Mathematik einsteigt. Es wird nicht nur erkl�rt, wof�ur wichtige Begriffe wie Big Data, machinelles Lernen oder Klassifikation stehen, sondern auch anschaulich...
Author
Publisher
Packt Publishing, Limited
Pub. Date
2022.
Language
English
Description
Explore supercharged machine learning techniques to take care of your data laundry loads Key Features Learn how to prepare data for machine learning processes Understand which algorithms are based on prediction objectives and the properties of the data Explore how to interpret and evaluate the results from machine learning Book Description Many individuals who know how to run machine learning algorithms do not have a good sense of the statistical...
Author
Publisher
Morgan Kaufmann, an imprint of Elsevier
Pub. Date
2019.
Language
English
Description
We live in a world in which huge volumes of data are being collected. The machine intelligence community has been very successful in turning this data into information. Taking the power of hybrid architectures as a starting point, analytics approaches can be upgraded. Meta-Analytics supplies an exhaustive set of patterns for data science to use on any machine learning based data analysis task. The book virtually ensures that at least one pattern will...
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