Mastering Scikit-Learn
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Book 1
Book 2
Book 3
Home > Computing and Information Technology > Computer science > Artificial intelligence > Neural networks and fuzzy systems > Mastering Scikit-Learn
Mastering Scikit-Learn

Mastering Scikit-Learn


     0     
5
4
3
2
1



Out of Stock


Notify me when this book is in stock
X
About the Book

Master the Art of Machine Learning with Scikit-Learn: Your Path from Data Scientist to ML Engineer
Are you ready to transform raw data into powerful, production-ready predictive models? Mastering Scikit-Learn is the definitive, hands-on guide for developers, data scientists, and engineers who want to go beyond the basics and build industrial-grade machine learning systems using the world's most popular Python library.
From the fundamentals of linear algebra to the complexities of distributed computing with Dask, this book provides a seamless, step-by-step journey through the entire machine learning lifecycle. Whether you are building your first regression model or deploying a high-performance text classifier, you will find exhaustive, straight-to-the-point prose that prioritizes clarity, scannability, and real-world application.
What's Inside the Complete Guide?
This book is meticulously structured to mirror the workflow of a professional machine learning project:

  • The Scikit-Learn Foundation: Master the core API, from the Estimator-Transformer interface to building robust, leak-proof Pipelines.
  • Advanced Feature Engineering: Learn the secrets of ColumnTransformer, polynomial features, and custom transformers to extract maximum signal from your data.
  • Unsupervised & Supervised Learning: Deep dives into Clustering (K-Means, DBSCAN), Dimensionality Reduction (PCA, t-SNE), and high-performance ensembles like HistGradientBoosting.
  • Natural Language Processing (NLP): Build end-to-end text classifiers and sentiment analysis engines using TfidfVectorizer and N-grams.
  • Time Series Forecasting: Master the art of lag features, rolling windows, and the TimeSeriesSplit strategy for temporal data.
  • Fairness & Ethics: Learn to identify bias using fairness metrics and build models that are not only accurate but also ethical and transparent.
  • High-Performance Scaling: Tackle "Big Data" with incremental learning (partial_fit), parallel processing with Joblib, and distributed clusters with Dask.
  • Production Deployment: Bridge the gap between research and reality with Model Serialization (Joblib/ONNX) and real-time API integration using FastAPI.
Why Choose This Book?
  • Developer-First Approach: Skip the academic fluff. Every chapter is written in clear, simple paragraphs with a focus on implementation and "hands-on" examples.
  • Real-World Illustrations: All code examples are drawn from official documentation and industry best practices, ensuring you learn the "official" way to build ML systems.
  • Comprehensive Capstone: Apply everything you've learned in an end-to-end Capstone Project, from problem definition to monitoring for data drift in production.
  • Troubleshooting & Math Refreshers: Includes essential appendices on the mathematical foundations of ML and a quick-reference guide for common coding pitfalls and error messages.
Who Is This Book For?
  • Python Developers looking to transition into the high-demand field of Machine Learning.
  • Data Scientists who want to professionalize their code and build scalable, production-ready pipelines.
  • Students and Researchers seeking a practical, comprehensive reference for the Scikit-Learn ecosystem.
Stop experimenting and start engineering. Elevate your career and build the future of intelligent systems with Mastering Scikit-Learn.


Best Sellers


Product Details
  • ISBN-13: 9798245924977
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • ISBN-10: 8245924970
  • Publisher Date: 27 Jan 2026


Similar Products

Add Photo
Add Photo

Customer Reviews

REVIEWS      0     
Click Here To Be The First to Review this Product
Mastering Scikit-Learn
Independently Published -
Mastering Scikit-Learn
Writing guidlines
We want to publish your review, so please:
  • keep your review on the product. Review's that defame author's character will be rejected.
  • Keep your review focused on the product.
  • Avoid writing about customer service. contact us instead if you have issue requiring immediate attention.
  • Refrain from mentioning competitors or the specific price you paid for the product.
  • Do not include any personally identifiable information, such as full names.

Mastering Scikit-Learn

Required fields are marked with *

Review Title*
Review
    Add Photo Add up to 6 photos
    Would you recommend this product to a friend?
    Tag this Book Read more
    Does your review contain spoilers?
    What type of reader best describes you?
    I agree to the terms & conditions
    You may receive emails regarding this submission. Any emails will include the ability to opt-out of future communications.

    CUSTOMER RATINGS AND REVIEWS AND QUESTIONS AND ANSWERS TERMS OF USE

    These Terms of Use govern your conduct associated with the Customer Ratings and Reviews and/or Questions and Answers service offered by Bookswagon (the "CRR Service").


    By submitting any content to Bookswagon, you guarantee that:
    • You are the sole author and owner of the intellectual property rights in the content;
    • All "moral rights" that you may have in such content have been voluntarily waived by you;
    • All content that you post is accurate;
    • You are at least 13 years old;
    • Use of the content you supply does not violate these Terms of Use and will not cause injury to any person or entity.
    You further agree that you may not submit any content:
    • That is known by you to be false, inaccurate or misleading;
    • That infringes any third party's copyright, patent, trademark, trade secret or other proprietary rights or rights of publicity or privacy;
    • That violates any law, statute, ordinance or regulation (including, but not limited to, those governing, consumer protection, unfair competition, anti-discrimination or false advertising);
    • That is, or may reasonably be considered to be, defamatory, libelous, hateful, racially or religiously biased or offensive, unlawfully threatening or unlawfully harassing to any individual, partnership or corporation;
    • For which you were compensated or granted any consideration by any unapproved third party;
    • That includes any information that references other websites, addresses, email addresses, contact information or phone numbers;
    • That contains any computer viruses, worms or other potentially damaging computer programs or files.
    You agree to indemnify and hold Bookswagon (and its officers, directors, agents, subsidiaries, joint ventures, employees and third-party service providers, including but not limited to Bazaarvoice, Inc.), harmless from all claims, demands, and damages (actual and consequential) of every kind and nature, known and unknown including reasonable attorneys' fees, arising out of a breach of your representations and warranties set forth above, or your violation of any law or the rights of a third party.


    For any content that you submit, you grant Bookswagon a perpetual, irrevocable, royalty-free, transferable right and license to use, copy, modify, delete in its entirety, adapt, publish, translate, create derivative works from and/or sell, transfer, and/or distribute such content and/or incorporate such content into any form, medium or technology throughout the world without compensation to you. Additionally,  Bookswagon may transfer or share any personal information that you submit with its third-party service providers, including but not limited to Bazaarvoice, Inc. in accordance with  Privacy Policy


    All content that you submit may be used at Bookswagon's sole discretion. Bookswagon reserves the right to change, condense, withhold publication, remove or delete any content on Bookswagon's website that Bookswagon deems, in its sole discretion, to violate the content guidelines or any other provision of these Terms of Use.  Bookswagon does not guarantee that you will have any recourse through Bookswagon to edit or delete any content you have submitted. Ratings and written comments are generally posted within two to four business days. However, Bookswagon reserves the right to remove or to refuse to post any submission to the extent authorized by law. You acknowledge that you, not Bookswagon, are responsible for the contents of your submission. None of the content that you submit shall be subject to any obligation of confidence on the part of Bookswagon, its agents, subsidiaries, affiliates, partners or third party service providers (including but not limited to Bazaarvoice, Inc.)and their respective directors, officers and employees.

    Accept


    Inspired by your browsing history


    Your review has been submitted!

    You've already reviewed this product!