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Practitioner’s Guide to Data Science (Chapman & Hall/CRC Data Science Series)
The Book provides a practical look at data science in real-world industry settings, covering both technical and soft skills not always found in traditional academic materials. Key features include a focus on big data cloud platforms like Spark using R and Python with provided code examples for hands-on learning, as well as discussions on data pre-processing, data wrangling, and various modeling techniques such as regression, regularization methods, and tree-based models like random forest and boosted trees. The text also offers insights into the history of data science, typical data science project cycles, and the different roles within a data science team. Finally, it touches upon deep learning, covering Feedforward, Convolutional, and Recurrent Neural Networks, along with discussions on databases and SQL.
You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cyber_security_summary
Get the Book now from Amazon:
https://www.amazon.com/Practitioners-Guide-Data-Science-Chapman/dp/0815354398?&linkCode=ll1&tag=cvthunderx-20&linkId=fcdf7ebbc5282cdec95235000c2e51ea&language=en_US&ref_=as_li_ss_tl
Discover our free courses in tech and cybersecurity, Start learning today:
https://linktr.ee/cybercode_academy
You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cyber_security_summary
Get the Book now from Amazon:
https://www.amazon.com/Practitioners-Guide-Data-Science-Chapman/dp/0815354398?&linkCode=ll1&tag=cvthunderx-20&linkId=fcdf7ebbc5282cdec95235000c2e51ea&language=en_US&ref_=as_li_ss_tl
Discover our free courses in tech and cybersecurity, Start learning today:
https://linktr.ee/cybercode_academy
View all episodes
By CyberSecurity Summary
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55 ratings
The Book provides a practical look at data science in real-world industry settings, covering both technical and soft skills not always found in traditional academic materials. Key features include a focus on big data cloud platforms like Spark using R and Python with provided code examples for hands-on learning, as well as discussions on data pre-processing, data wrangling, and various modeling techniques such as regression, regularization methods, and tree-based models like random forest and boosted trees. The text also offers insights into the history of data science, typical data science project cycles, and the different roles within a data science team. Finally, it touches upon deep learning, covering Feedforward, Convolutional, and Recurrent Neural Networks, along with discussions on databases and SQL.
You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cyber_security_summary
Get the Book now from Amazon:
https://www.amazon.com/Practitioners-Guide-Data-Science-Chapman/dp/0815354398?&linkCode=ll1&tag=cvthunderx-20&linkId=fcdf7ebbc5282cdec95235000c2e51ea&language=en_US&ref_=as_li_ss_tl
Discover our free courses in tech and cybersecurity, Start learning today:
https://linktr.ee/cybercode_academy
You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cyber_security_summary
Get the Book now from Amazon:
https://www.amazon.com/Practitioners-Guide-Data-Science-Chapman/dp/0815354398?&linkCode=ll1&tag=cvthunderx-20&linkId=fcdf7ebbc5282cdec95235000c2e51ea&language=en_US&ref_=as_li_ss_tl
Discover our free courses in tech and cybersecurity, Start learning today:
https://linktr.ee/cybercode_academy
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