Data science bookcamp: five real-world Python projects
Valuable and accessible... a solid foundation for anyone aspiring to be a data scientist. Amaresh Rajasekharan, IBM Corporation Learn data science with Python by building five real-world projects! Experiment with card game predictions, tracking disease outbreaks, and more, as you build a flexible an...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Weitere beteiligte Personen: | |
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
[Shelter Island, New York]
Manning Publications Co.
2021
|
| Ausgabe: | [First edition]. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781617296253AU/?ar |
| Zusammenfassung: | Valuable and accessible... a solid foundation for anyone aspiring to be a data scientist. Amaresh Rajasekharan, IBM Corporation Learn data science with Python by building five real-world projects! Experiment with card game predictions, tracking disease outbreaks, and more, as you build a flexible and intuitive understanding of data science. In Data Science Bookcamp you will find: Techniques for computing and plotting probabilities Statistical analysis using Scipy How to organize datasets with clustering algorithms How to visualize complex multi-variable datasets How to train a decision tree machine learning algorithm In Data Science Bookcamp you'll test and build your knowledge of Python with the kind of open-ended problems that professional data scientists work on every day. Downloadable data sets and thoroughly-explained solutions help you lock in what you've learned, building your confidence and making you ready for an exciting new data science career. about the technology A data science project has a lot of moving parts, and it takes practice and skill to get all the code, algorithms, datasets, formats, and visualizations working together harmoniously. This unique book guides you through five realistic projects, including tracking disease outbreaks from news headlines, analyzing social networks, and finding relevant patterns in ad click data. about the book Data Science Bookcamp doesn't stop with surface-level theory and toy examples. As you work through each project, you'll learn how to troubleshoot common problems like missing data, messy data, and algorithms that don't quite fit the model you're building. You'll appreciate the detailed setup instructions and the fully explained solutions that highlight common failure points. In the end, you'll be confident in your skills because you can see the results. about the audience For readers who know the basics of Python. No prior data science or machine learning skills required. about the author Leonard Apeltsin is the Head of Data Science at Anomaly, where his team applies advanced analytics to uncover healthcare fraud, waste, and abuse. Really good introduction of statistical data science concepts. A must-have for every beginner! Simone Sguazza, University of Applied Sciences and Arts of Southern Switzerland A full-fledged tutorial in data science including common Python libraries and language tricks! Jean-François Morin, Laval University This book is a complete package for understanding how the data science process works end to end. |
| Beschreibung: | Online resource; title from title details screen (O'Reilly, viewed May 2, 2022) |
| Umfang: | 1 Online-Ressource (1 sound file (18 hr., 1 min.)) |
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| spelling | Apeltsin, Leonard VerfasserIn aut Data science bookcamp five real-world Python projects Leonard Apeltsin Five real-world Python projects [First edition]. [Shelter Island, New York] Manning Publications Co. 2021 1 Online-Ressource (1 sound file (18 hr., 1 min.)) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Online resource; title from title details screen (O'Reilly, viewed May 2, 2022) Valuable and accessible... a solid foundation for anyone aspiring to be a data scientist. Amaresh Rajasekharan, IBM Corporation Learn data science with Python by building five real-world projects! Experiment with card game predictions, tracking disease outbreaks, and more, as you build a flexible and intuitive understanding of data science. In Data Science Bookcamp you will find: Techniques for computing and plotting probabilities Statistical analysis using Scipy How to organize datasets with clustering algorithms How to visualize complex multi-variable datasets How to train a decision tree machine learning algorithm In Data Science Bookcamp you'll test and build your knowledge of Python with the kind of open-ended problems that professional data scientists work on every day. Downloadable data sets and thoroughly-explained solutions help you lock in what you've learned, building your confidence and making you ready for an exciting new data science career. about the technology A data science project has a lot of moving parts, and it takes practice and skill to get all the code, algorithms, datasets, formats, and visualizations working together harmoniously. This unique book guides you through five realistic projects, including tracking disease outbreaks from news headlines, analyzing social networks, and finding relevant patterns in ad click data. about the book Data Science Bookcamp doesn't stop with surface-level theory and toy examples. As you work through each project, you'll learn how to troubleshoot common problems like missing data, messy data, and algorithms that don't quite fit the model you're building. You'll appreciate the detailed setup instructions and the fully explained solutions that highlight common failure points. In the end, you'll be confident in your skills because you can see the results. about the audience For readers who know the basics of Python. No prior data science or machine learning skills required. about the author Leonard Apeltsin is the Head of Data Science at Anomaly, where his team applies advanced analytics to uncover healthcare fraud, waste, and abuse. Really good introduction of statistical data science concepts. A must-have for every beginner! Simone Sguazza, University of Applied Sciences and Arts of Southern Switzerland A full-fledged tutorial in data science including common Python libraries and language tricks! Jean-François Morin, Laval University This book is a complete package for understanding how the data science process works end to end. Data mining Data sets Python (Computer program language) Data Mining Datasets as Topic Exploration de données (Informatique) Jeux de données Python (Langage de programmation) Downloadable audio books Audiobooks Livres audio Brierley, Julie ErzählerIn nrt |
| spellingShingle | Apeltsin, Leonard Data science bookcamp five real-world Python projects Data mining Data sets Python (Computer program language) Data Mining Datasets as Topic Exploration de données (Informatique) Jeux de données Python (Langage de programmation) Downloadable audio books Audiobooks Livres audio |
| title | Data science bookcamp five real-world Python projects |
| title_alt | Five real-world Python projects |
| title_auth | Data science bookcamp five real-world Python projects |
| title_exact_search | Data science bookcamp five real-world Python projects |
| title_full | Data science bookcamp five real-world Python projects Leonard Apeltsin |
| title_fullStr | Data science bookcamp five real-world Python projects Leonard Apeltsin |
| title_full_unstemmed | Data science bookcamp five real-world Python projects Leonard Apeltsin |
| title_short | Data science bookcamp |
| title_sort | data science bookcamp five real world python projects |
| title_sub | five real-world Python projects |
| topic | Data mining Data sets Python (Computer program language) Data Mining Datasets as Topic Exploration de données (Informatique) Jeux de données Python (Langage de programmation) Downloadable audio books Audiobooks Livres audio |
| topic_facet | Data mining Data sets Python (Computer program language) Data Mining Datasets as Topic Exploration de données (Informatique) Jeux de données Python (Langage de programmation) Downloadable audio books Audiobooks Livres audio |
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