Books › Computers & Technology › Databases & Big Data

Time Series Forecasting in Python

Name: Time Series Forecasting in Python
Price: 33.04 USD
Availability: InStock
Rating: 4.5 (12 reviews)

4.5 of 5 Stars: Databases & Big Data - Time Series Forecasting in Python

$33.04

Buying Options

Description

Book Synopsis: Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting.In Time Series Forecasting in Python you will learn how to: Recognize a time series forecasting problem and build a performant predictive model Create univariate forecasting models that account for seasonal effects and external variables Build multivariate forecasting models to predict many time series at once Leverage large datasets by using deep learning for forecasting time series Automate the forecasting process Time Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You’ll explore interesting real-world datasets like Google’s daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology You can predict the future—with a little help from Python, deep learning, and time series data! Time series forecasting is a technique for modeling time-centric data to identify upcoming events. New Python libraries and powerful deep learning tools make accurate time series forecasts easier than ever before.

About the book Time Series Forecasting in Python teaches you how to get immediate, meaningful predictions from time-based data such as logs, customer analytics, and other event streams. In this accessible book, you’ll learn statistical and deep learning methods for time series forecasting, fully demonstrated with annotated Python code. Develop your skills with projects like predicting the future volume of drug prescriptions, and you’ll soon be ready to build your own accurate, insightful forecasts.

What’s inside Create models for seasonal effects and external variables Multivariate forecasting models to predict multiple time series Deep learning for large datasets Automate the forecasting process

About the reader For data scientists familiar with Python and TensorFlow.

About the author Marco Peixeiro is a seasoned data science instructor who has worked as a data scientist for one of Canada’s largest banks.

Table of Contents
PART 1 TIME WAITS FOR NO ONE
1 Understanding time series forecasting
2 A naive prediction of the future
3 Going on a random walk
PART 2 FORECASTING WITH STATISTICAL MODELS
4 Modeling a moving average process
5 Modeling an autoregressive process
6 Modeling complex time series
7 Forecasting non-stationary time series
8 Accounting for seasonality
9 Adding external variables to our model
10 Forecasting multiple time series
11 Capstone: Forecasting the number of antidiabetic drug prescriptions in Australia
PART 3 LARGE-SCALE FORECASTING WITH DEEP LEARNING
12 Introducing deep learning for time series forecasting
13 Data windowing and creating baselines for deep learning
14 Baby steps with deep learning
15 Remembering the past with LSTM
16 Filtering a time series with CNN
17 Using predictions to make more predictions
18 Capstone: Forecasting the electric power consumption of a household
PART 4 AUTOMATING FORECASTING AT SCALE
19 Automating time series forecasting with Prophet
20 Capstone: Forecasting the monthly average retail price of steak in Canada
21 Going above and beyond

Details

Are you ready to take your data analysis and predictive modeling to the next level? Introducing Time Series Forecasting in Python, the ultimate guide to building powerful predictive models from time-based data. With this book, you'll learn how to recognize time series forecasting problems and create high-performance predictive models using statistical and deep learning approaches.

One of the key features of Time Series Forecasting in Python is its focus on helping you create models that are not only relevant and useful, but also easy to implement with Python. You'll explore real-world datasets, such as Google's daily stock price and economic data for the USA, and quickly progress from the basics to developing large-scale models using cutting-edge tools like TensorFlow.

Whether you're looking to predict stock prices, customer behavior, or any other time-based patterns, Time Series Forecasting in Python has got you covered. By leveraging Python, deep learning, and time series data, you'll be able to forecast the future with unprecedented accuracy.

Don't miss out on this opportunity to enhance your data science skills. Purchase the print book today and receive a free eBook in PDF, Kindle, and ePub formats from Manning Publications. Take the first step towards becoming a time series forecasting expert!

Why rely on guesswork when you can accurately predict the future? Time Series Forecasting in Python offers you the tools and techniques to make immediate, meaningful predictions from time-based data. Whether you're analyzing logs, customer analytics, or event streams, this book will empower you to develop statistical and deep learning models for time series forecasting.

In this accessible book, you'll find annotated Python code that fully demonstrates various forecasting methods. You'll learn how to create models that account for seasonal effects and external variables, predict multiple time series simultaneously, and even leverage deep learning techniques for large datasets.

Throughout your journey with Time Series Forecasting in Python, you'll engage in hands-on projects, such as predicting the future volume of drug prescriptions. By practicing with real-world examples, you'll gain the skills you need to build accurate and insightful forecasts on your own.

If you're a data scientist familiar with Python and TensorFlow, this book is your ticket to mastering time series forecasting. Take your data analysis skills to new heights and unlock the power of predictive modeling. Don't wait—start your journey today!

Are you ready to unlock the future with Python and time series data? Time Series Forecasting in Python is your ultimate guide to automating the forecasting process and gaining valuable insights from time-based data. Let Python and deep learning tools lead the way in accurate and efficient time series forecasting.

This comprehensive book covers everything you need to know to create forecasts that factor in seasonal effects and external variables. You'll even learn how to predict multiple time series at once, thanks to the power of multivariate forecasting models. And with the help of deep learning algorithms, analyzing and predicting large datasets becomes a breeze.

Time Series Forecasting in Python is tailor-made for data scientists who are already familiar with Python and TensorFlow. Written by Marco Peixeiro, a seasoned data science instructor and industry expert, this book will equip you with the skills and knowledge to excel in time series forecasting.

Don't let the future remain a mystery—take control of time-centric data and unlock its predictive potential. Act now and purchase the print book to receive a free eBook in PDF, Kindle, and ePub formats from Manning Publications. Start your journey toward accurate forecasting today!

See All Buying Options...

More Details...