The data science workshop : a new, interactive approach to learning data science / by Anthony So [and four others].
Material type:![Computer file](/opac-tmpl/lib/famfamfam/CF.png)
- text
- computer
- online resource
- 9781838981266 (e-book)
- Q325.5 So1 2020
Item type | Current library | Collection | Call number | Materials specified | Status | Notes | Date due | Barcode |
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Ladislao N. Diwa Memorial Library Multimedia Section | Non-fiction | OEBP Q325.5 So1 2020 (Browse shelf(Opens below)) | Available | PAV | OEBP000324 | ||
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Ladislao N. Diwa Memorial Library Multimedia Section | Non-fiction | EB Q325.5 So1 2020 (Browse shelf(Opens below)) | Room use only | PAV | EB000324 |
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OEBP P325.5 C65 St6 2021 Context and coherence : the logic and grammar of prominence / | OEBP PE1128.A2 En3 2020 English for specific purposes instruction and research : current practices, challenges and innovations / | OEBP PN56.M54 R82 2020 Modernism and its environments / | OEBP Q325.5 So1 2020 The data science workshop : a new, interactive approach to learning data science / | OEBP QA75.5 Em3 2020 Emerging trends in electrical, communications, and information technologies : Proceedings of ICECIT-2018 / | OEBP QA76.6 A54D34 2022 ASP.NET Core 6 and Angular : full-stack web development with ASP.NET 6 and Angular 13 / | OEBP QA76.9 A25Oz5 2022 Cybersecurity leadership demystified a comprehensive guide to becoming : a comprehensive guide to becoming a world-class modern cybersecurity leader and global CISO / |
https://portal.igpublish.com/iglibrary/ is required to read this e-book.
Include index
1. Introduction to data science in Python -- 2. Regression -- 3. Binary classification -- 4. Multiclass classification with random forest -- 5. Performing your first cluster analysis -- 6. How to assess performance
-- 7. The generalization of machine learning models -- 8. Hyperparameter tuning -- 9. Interpreting a machine learning model -- 10. Analyzing a dataset -- 11. Data preparation -- 12. Feature engineering --
13. Imbalanced datasets -- 14. Dimensionality reduction -- 15. Ensemble learning -- 16. Machine learning pipelines -- 17. Automated feature engineering
Cut through the noise and get real results with a step-by-step approach to data science Key Features Ideal for the data science beginner who is getting started for the first time A data science tutorial with step-by-step exercises and activities that help build key skills Structured to let you progress at your own pace, on your own terms Use your physical print copy to redeem free access to the online interactive edition Book Description You already know you want to learn data science, and a smarter way to learn data science is to learn by doing. The Data Science Workshop focuses on building up your practical skills so that you can understand how to develop simple machine learning models in Python or even build an advanced model for detecting potential bank frauds with effective modern data science. You'll learn from real examples that lead to real results. Throughout The Data Science Workshop, you'll take an engaging step-by-step approach to understanding data science. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend training a model using sci-kit learn. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical print copy of The Data Science Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your data science book. Fast-paced and direct, The Data Science Workshop is the ideal companion for data science beginners. You'll learn about machine learning algorithms like a data scientist, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead. What you will learn Find out the key differences between supervised and unsupervised learning Manipulate and analyze data using scikit-learn and pandas libraries Learn about different algorithms such as regression, classification, and clustering Discover advanced techniques to improve model ensembling and accuracy Speed up the process of creating new features with automated feature tool Simplify machine learning using open source Python packages Who this book is for Our goal at Packt is to help you be successful, in whatever it is you choose to do. The Data Science Workshop is an ideal data science tutorial for the data science beginner who is just getting started. Pick up a Workshop today and let Packt help you develop skills that stick with you for life.
Fund 164 CE-Logic Purchased April 14, 2022 OEBP000324 Carmona Campus PHP No Price 0000 0000