scikit-learn : Machine Learning Simplified
Language: English
Published by Packt Publishing Limited, GB, 2025
- Softcover
- New
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
AbeBooks seller since June 11, 2025
Condition: New
£ 105.05
Quantity: Over 20 available
Add to basketItem description from seller
No detailed description available for "scikit-learn : Machine Learning Simplified".
Seller Inventory # LU-9781788833479
- Title
- scikit-learn : Machine Learning Simplified
- Author
- Trent Hauck, Guillermo Moncecchi, Raul G Tompson, Gavin Hackeling
- Publisher
- Packt Publishing Limited, GB
- Publication year
- 2025
- Condition
- New
- Binding
- Digital
- Language
- English
- ISBN 10
- 1788833473
- ISBN 13
- 9781788833479
Implement scikit-learn into every step of the data science pipeline
Key Features:
- Use Python and scikit-learn to create intelligent applications
- Discover how to apply algorithms in a variety of situations to tackle common and not-so common challenges in the machine learning domain
- A practical, example-based guide to help you gain expertise in implementing and evaluating machine learning systems using scikit-learn
Book Description:
Machine learning, the art of creating applications that learn from experience and data, has been around for many years. Python is quickly becoming the go-to language for analysts and data scientists due to its simplicity and flexibility; moreover, within the Python data space, scikit-learn is the unequivocal choice for machine learning. The course combines an introduction to some of the main concepts and methods in machine learning with practical, hands-on examples of real-world problems. The course starts by walking through different methods to prepare your data-be it a dataset with missing values or text columns that require the categories to be turned into indicator variables. After the data is ready, you'll learn different techniques aligned with different objectives-be it a dataset with known outcomes such as sales by state, or more complicated problems such as clustering similar customers. Finally, you'll learn how to polish your algorithm to ensure that it's both accurate and resilient to new datasets. You will learn to incorporate machine learning in your applications. Ranging from handwritten digit recognition to document classification, examples are solved step-by-step using scikit-learn and Python. By the end of this course you will have learned how to build applications that learn from experience, by applying the main concepts and techniques of machine learning.
What You Will Learn:
- Review fundamental concepts including supervised and unsupervised experiences, common tasks, and performance metrics
- Classify objects (from documents to human faces and flower species) based on some of their features, using a variety of methods from Support Vector Machines to Naïve Bayes
- Use Decision Trees to explain the main causes of certain phenomena such as passenger survival on the Titanic
- Evaluate the performance of machine learning systems in common tasks
- Master algorithms of various levels of complexity and learn how to analyze data at the same time
- Learn just enough math to think about the connections between various algorithms
- Customize machine learning algorithms to fit your problem, and learn how to modify them when the situation calls for it
- Incorporate other packages from the Python ecosystem to munge and visualize your dataset
- Improve the way you build your models using parallelization techniques
Who this book is for:
If you are a programmer and want to explore machine learning and data-based methods to build intelligent applications and enhance your programming skills, this is the course for you. No previous experience with machine-learning algorithms is required.
"Synopsis" may belong to another edition of this title.
About the Author
Guillermo Moncecchi is a Natural Language Processing researcher at the Universidad de la Republica of Uruguay. He received a PhD in Informatics from the Universidad de la Republica, Uruguay and a Ph.D in Language Sciences from the Universite Paris Ouest, France. He has participated in several international projects on NLP. He has almost 15 years of teaching experience on Automata Theory, Natural Language Processing, and Machine Learning. He also works as Head Developer at the Montevideo Council and has lead the development of several public services for the council, particularly in the Geographical Information Systems area. He is one of the Montevideo Open Data movement leaders, promoting the publication and exploitation of the city's data.
Trent Hauck is a data scientist living and working in the Seattle area. He grew up in Wichita, Kansas and received his undergraduate and graduate degrees from the University of Kansas. He is the author of the book Instant Data Intensive Apps with pandas How-to, Packt Publishing-a book that can get you up to speed quickly with pandas and other associated technologies.
Gavin Hackeling develops machine learning services for large-scale documents and image classification at an advertising network in New York. He received his Master's degree from New York University's Interactive Telecommunications Program, and his Bachelor's degree from the University of North Carolina.
"About the title" may belong to another edition of this title.
Rarewaves.com UK
London, United Kingdom
AbeBooks seller since June 11, 2025
Shipping rates from United Kingdom to U.S.A.
| Item | 60 to 60 business days | 60 to 60 business days |
|---|---|---|
| First item | £ 65.00 | £ 100.00 |
Payment methods
Seller's business information
RAREWAVES.COM LIMITED
Elsley Court, 20-22 Great Titchfield Street
London, United Kingdom W1W 8BE
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 Rarewaves.com UK, Unit 144 The Lightbox, 111 Power Road, W4 5PY, London, London, United Kingdom, 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
Please note that we do not offer Priority shipping to any country.
We currently do not ship to the below countries:
Russia
Belarus
Ukraine
Please do not attempt to place orders with any of these countries as a ship to address - they will be cancelled.