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Computer Science - Practical Time Series Analysis: Prediction with Statistics and Machine Learning

Description

Book Synopsis: Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challenges in time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance Read more

Details

Are you struggling to make sense of the massive amounts of time series data that your business collects? Look no further. Our new book "Practical Time Series Analysis: Prediction with Statistics and Machine Learning" is here to help you navigate the complexities of time series analysis. With the advent of the internet of things and the digitalization of industries like healthcare and smart cities, time series analysis has become increasingly important.

Written by renowned author Aileen Nielsen, this practical guide offers a comprehensive introduction to time series analysis in both R and Python. Whether you're a data scientist, software engineer, or researcher, you'll find all the tools and techniques you need to tackle the most common data engineering and analysis challenges in time series. From finding and wrangling time series data, to measuring error and forecasting with machine or deep learning, this book covers it all.

But what sets this book apart is its focus on practicality. Nielsen combines traditional statistical methods with the latest machine learning techniques to provide you with a well-rounded approach to time series analysis. By using real-world use cases and providing step-by-step instructions, she ensures that you can put your newfound knowledge into practice immediately.

Don't miss out on the opportunity to confidently analyze and leverage time series data for your business. Order your copy of "Practical Time Series Analysis: Prediction with Statistics and Machine Learning" today and take your data analysis skills to the next level.

Order now and unlock the full potential of time series analysis!

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