Machine Learning for Imbalanced Data
Language: English
Published by Packt Publishing, 2023
- Softcover
- New
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
AbeBooks seller since June 11, 1999
Condition: New
£ 45.11
Quantity: Over 20 available
Add to basketItem description from seller
New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Seller Inventory # L0-9781801070836
- Title
- Machine Learning for Imbalanced Data
- Author
- Kumar Abhishek
- Publisher
- Packt Publishing
- Publication year
- 2023
- Condition
- New
- Binding
- PAP
- Language
- English
- ISBN 10
- 1801070830
- ISBN 13
- 9781801070836
- Item weight
- 711 grams
Take your machine learning expertise to the next level with this essential guide, utilizing libraries like imbalanced-learn, PyTorch, scikit-learn, pandas, and NumPy to maximize model performance and tackle imbalanced data
Key Features
- Understand how to use modern machine learning frameworks with detailed explanations, illustrations, and code samples
- Learn cutting-edge deep learning techniques to overcome data imbalance
- Explore different methods for dealing with skewed data in ML and DL applications
- Purchase of the print or Kindle book includes a free eBook in the PDF format
Book Description
As machine learning practitioners, we often encounter imbalanced datasets in which one class has considerably fewer instances than the other. Many machine learning algorithms assume an equilibrium between majority and minority classes, leading to suboptimal performance on imbalanced data. This comprehensive guide helps you address this class imbalance to significantly improve model performance.
Machine Learning for Imbalanced Data begins by introducing you to the challenges posed by imbalanced datasets and the importance of addressing these issues. It then guides you through techniques that enhance the performance of classical machine learning models when using imbalanced data, including various sampling and cost-sensitive learning methods.
As you progress, you’ll delve into similar and more advanced techniques for deep learning models, employing PyTorch as the primary framework. Throughout the book, hands-on examples will provide working and reproducible code that’ll demonstrate the practical implementation of each technique.
By the end of this book, you’ll be adept at identifying and addressing class imbalances and confidently applying various techniques, including sampling, cost-sensitive techniques, and threshold adjustment, while using traditional machine learning or deep learning models.
What you will learn
- Use imbalanced data in your machine learning models effectively
- Explore the metrics used when classes are imbalanced
- Understand how and when to apply various sampling methods such as over-sampling and under-sampling
- Apply data-based, algorithm-based, and hybrid approaches to deal with class imbalance
- Combine and choose from various options for data balancing while avoiding common pitfalls
- Understand the concepts of model calibration and threshold adjustment in the context of dealing with imbalanced datasets
Who this book is for
This book is for machine learning practitioners who want to effectively address the challenges of imbalanced datasets in their projects. Data scientists, machine learning engineers/scientists, research scientists/engineers, and data scientists/engineers will find this book helpful. Though complete beginners are welcome to read this book, some familiarity with core machine learning concepts will help readers maximize the benefits and insights gained from this comprehensive resource.
Table of Contents
- Introduction to Data Imbalance in Machine Learning
- Oversampling Methods
- Undersampling Methods
- Ensemble Methods
- Cost-Sensitive Learning
- Data Imbalance in Deep Learning
- Data-Level Deep Learning Methods
- Algorithm-Level Deep Learning Techniques
- Hybrid Deep Learning Methods
- Model Calibration
- Appendix
"Synopsis" may belong to another edition of this title.
About the Author
Kumar Abhishek is a seasoned Senior Machine Learning Engineer at Expedia Group, US, specializing in risk analysis and fraud detection for Expedia brands. With over a decade of experience at companies such as Microsoft, Amazon, and a Bay Area startup, Kumar holds an MS in Computer Science from the University of Florida.
Dr. Mounir Abdelaziz is a deep learning researcher specializing in computer vision applications. He holds a Ph.D. in computer science and technology from Central South University, China. During his Ph.D. journey, he developed innovative algorithms to address practical computer vision challenges. He has also authored numerous research articles in the field of few-shot learning for image classification.
"About the title" may belong to another edition of this title.
PBShop.store UK
Fairford, GLOS, United Kingdom
AbeBooks seller since June 11, 1999
Shipping rates from United Kingdom to U.S.A.
| Item | 10 to 20 business days | 10 to 20 business days |
|---|---|---|
| First item | £ 5.02 | £ 5.02 |
Payment methods
Store description
**Please note our transit times are from the date of dispatch.** We first started out as “The Paperback Exchange,” a chain of physical bookstores where we would part exchange your beloved books for new stories to transport you to faraway places. However, as shopping started to evolve to online shops and marketplaces, we bid our stores goodbye to become “PBShop.” This transition has only allowed us to blossom as we now ship thousands of titles to book lovers across the globe. We pride ourselves in being a community of local book lovers which allows our passion and devotion to shine in everything we do. In 2020 we not only celebrated our 20th birthday but our 1st birthday as being completely employee owned after becoming an E.O.T in September 2019. We are proud to be different and embrace standing apart on a book mountain by working from a virtual inventory which allows us to provide thousands of books that may be difficult to get for your bookshelf or your studies. Working with a number of different suppliers allows us to explore other avenues such as puzzles, sheet music and even stationery so we really do have something for everyone. Life is about being versatile in all realms of existence. If this is your first purchase with us, or you are a returning customer, we would like to welcome you to the PBShop family, for there is no friend as loyal as a book. We are a company who put our customers at the centre of everything we do as we understand the importance of reading because once you learn to read, you will forever be free. There are a whole lot of things in this world of ours that we are yet to explore, which is why we will forever inspire curious minds.…
Specialty
Hardbacks, PaperbacksSeller's business information
Pbshop.co.uk
Unit 22 Horcott Industrial Estate, Horcott Road
Fairford, United Kingdom GL7 4BX
Terms of sale
Returns Policy
We ask all customers to contact us for authorisation should they wish to return their order. Orders returned without authorisation may not be credited.
If you wish to return, please contact us within 14 days of receiving your order to obtain authorisation.
Returns requested beyond this time will not be authorised.
Our team will provide full instructions on how to return your order and once received our returns department will process your refund.
Please note the cost to return any unwanted order to us is borne by the buyer.
Should your order arrive damaged, not as advertised or faulty, we must be advised of this within 14 days of delivery. Please contact us so we can find the best solution for you.
Our Customer Care Team can be contacted by emailing alborders@paperbackshop.co.uk, or by calling our UK Office on +441285 712 917. We are available 9:00am till 5:30pm GMT Monday to Friday.
Right of withdrawal
If you are a consumer you can withdraw from 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 withdrawal
Statutory right to withdraw
You have the right to withdraw from this contract within 14 days without giving any reason.
The withdrawal 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 last good or the last lot or piece.
To exercise the right of withdrawal, electronically fill in and submit a clear statement on our website, under "My Purchases" in "My Account". We will communicate to you an acknowledgement of receipt of such a withdrawal on a durable medium (e.g. by e-mail) without delay.
To meet the withdrawal deadline, it is sufficient for you to send your communication concerning your exercise of the right of withdrawal before the withdrawal period has expired.
Effects of withdrawal
If you withdraw from 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 withdraw from this 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 PBShop.store UK, Fairford, United Kingdom, +44 1285 712917, without undue delay and in any event not later than 14 days from the day on which you communicate your withdrawal 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 withdrawal
The right of withdrawal 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 withdraw once delivery had started.
Shipping terms
Orders are shipped from our UK warehouse. Delivery thereafter is between 4 and 14 business days. Please contact us if you have any queries about our services or products.