Title: Machine Learning for Time-Series with Python: Forecast, predict, and detect anomalies with state-of-the-art machine learning methods
Publisher: Packt Publishing, Limited
Publication Date: 2021
Language: English
ISBN 10: 1801819629
ISBN 13: 9781801819626
Binding: Soft cover
Condition: New

About this title

Synopsis

Become proficient in deriving insights from time-series data and analyzing a model’s performance

Key Features

Explore popular and modern machine learning methods including the latest online and deep learning algorithms
Learn to increase the accuracy of your predictions by matching the right model with the right problem
Master time-series via real-world case studies on operations management, digital marketing, finance, and healthcare

Book Description

Machine learning has emerged as a powerful tool to understand hidden complexities in time-series datasets, which frequently need to be analyzed in areas as diverse as healthcare, economics, digital marketing, and social sciences. These datasets are essential for forecasting and predicting outcomes or for detecting anomalies to support informed decision making.

This book covers Python basics for time-series and builds your understanding of traditional autoregressive models as well as modern non-parametric models. You will become confident with loading time-series datasets from any source, deep learning models like recurrent neural networks and causal convolutional network models, and gradient boosting with feature engineering.

Machine Learning for Time-Series with Python explains the theory behind several useful models and guides you in matching the right model to the right problem. The book also includes real-world case studies covering weather, traffic, biking, and stock market data.

By the end of this book, you will be proficient in effectively analyzing time-series datasets with machine learning principles.

What you will learn

Understand the main classes of time-series and learn how to detect outliers and patterns
Choose the right method to solve time-series problems
Characterize seasonal and correlation patterns through autocorrelation and statistical techniques
Get to grips with time-series data visualization
Understand classical time-series models like ARMA and ARIMA
Implement deep learning models, like Gaussian processes, transformers, and state-of-the-art machine learning models
Become familiar with many libraries like Prophet, XGboost, and TensorFlow

Who this book is for

This book is ideal for data analysts, data scientists, and Python developers who are looking to perform time-series analysis to effectively predict outcomes. Basic knowledge of the Python language is essential. Familiarity with statistics is desirable.

Introduction to Time-Series with Python
Time-Series Analysis with Python
Preprocessing Time-Series
Introduction to Machine Learning for Time Series
Forecasting with Moving Averages and Autoregressive Models
Unsupervised Methods for Time-Series
Machine Learning Models for Time-Series
Online Learning for Time-Series
Probabilistic Models for Time-Series
Deep Learning for Time-Series
Reinforcement Learning for Time-Series
Multivariate Forecasting

About the Author

Ben Auffarth is a full-stack data scientist who has >15 years of work experience. With a background and Ph.D. in computational and cognitive neuroscience from one of Europe's top engineering universities, he has designed and conducted wet lab experiments on cell cultures, analyzed experiments with terabytes of data, run brain models on IBM supercomputers with up to 64k cores, built production systems processing hundreds of thousands of transactions per day, and trained neural networks on millions of text documents. In his work, he often notices a lack of appreciation for the importance of time-related factors, a deficit he wanted to address in this book. He co-founded and is the former president of Data Science Speakers, London.

"About this title" may belong to another edition of this title.

Store Description

I mainly carry imported books from South East Asia / South Asia for readers of all Age Groups.

Visit Seller's Storefront

Seller's business information

PLETOS INC
6931 51st Avenue, WOODSIDE, Woodside, NY, 11377, U.S.A.

Sale & Shipping Terms

Terms of Sale

We accept return for those books which are received damamged. Though we take appropriate care in packaing to avoid such situation.

Right of cancellation

If you are a consumer you can cancel the contract in accordance with the following. Consumer means any natural person who is acting for purposes which are outside his trade, business, craft or profession.

INFORMATION REGARDING THE RIGHT OF CANCELLATION

Statutory Right to cancel

You have the right to cancel this contract within 14 days without giving any reason.

The cancellation period will expire after 14 days from the day on which you acquire, or a third party other than the carrier and indicated by you acquires, physical possession of the the last good or the last lot or piece.

To exercise the right to cancel, you must inform us, Books Puddle, 244 Madison Ave, Suite # 405, 10016, New York, New York, U.S.A., +1 7183015977, of your decision to cancel this contract by a clear statement (e.g. a letter sent by post, fax or e-mail). You may use the attached model cancellation form, but it is not obligatory. You can also electronically fill in and submit a clear statement on our website, under "My Purchases" in "My Account". If you use this option, we will communicate to you an acknowledgement of receipt of such a cancellation on a durable medium (e.g. by e-mail) without delay.

To meet the cancellation deadline, it is sufficient for you to send your communication concerning your exercise of the right to cancel before the cancellation period has expired.

Effects of cancellation

If you cancel this contract, we will reimburse to you all payments received from you, including the costs of delivery (except for the supplementary costs arising if you chose a type of delivery other than the least expensive type of standard delivery offered by us).

We may make a deduction from the reimbursement for loss in value of any goods supplied, if the loss is the result of unnecessary handling by you.

We will make the reimbursement without undue delay, and not later than 14 days after the day on which we are informed about your decision to cancel with contract.

We will make the reimbursement using the same means of payment as you used for the initial transaction, unless you have expressly agreed otherwise; in any event, you will not incur any fees as a result of such reimbursement.

We may withhold reimbursement until we have received the goods back or you have supplied evidence of having sent back the goods, whichever is the earliest.

You shall send back the goods or hand them over to us or Books Puddle, 244 Madison Ave, Suite # 405, 10016, New York, New York, U.S.A., +1 7183015977, without undue delay and in any event not later than 14 days from the day on which you communicate your cancellation from this contract to us. The deadline is met if you send back the goods before the period of 14 days has expired. You will have to bear the direct cost of returning the goods. You are only liable for any diminished value of the goods resulting from the handling other than what is necessary to establish the nature, characteristics and functioning of the goods.

Exceptions to the right of cancellation

The right of cancellation does not apply to:

the delivery of newspapers, journals or magazines with the exception of subscription contracts; and
the supply of digital content which is not supplied on a tangible medium (e.g. on a CD or DVD) if you accepted when you placed your order that we could start to deliver it, and that you could not cancel it once delivery had started.

Model withdrawal form

(complete and return this form only if you wish to withdraw from the contract)

To: (Books Puddle, 244 Madison Ave, Suite # 405, 10016, New York, New York, U.S.A., +1 7183015977)

I/We (*) hereby give notice that I/We (*) withdraw from my/our (*) contract of sale of the following goods (*)/for the provision of the following goods (*)/for the provision of the following service (*),

Ordered on (*)/received on (*)

Name of consumer(s)

Address of consumer(s)

Signature of consumer(s) (only if this form is notified on paper)

Date

* Delete as appropriate.

Shipping Terms

Shipping rates within U.S.A.

Shipping rates within U.S.A.
Order quantity	12 to 19 business days	12 to 14 business days
First item	� 2.93	� 5.13

Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.