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Doing Data Science: Straight Talk from the Frontline
offers an overview of data science, drawing from a book based on a university course. It explores various algorithms and models such as linear and logistic regression, Naive Bayes, k-means, and singular value decomposition, providing practical applications like spam filtering and recommendation engines. The sources also discuss essential concepts including exploratory data analysis, feature selection, data visualization, and the challenges of working with Big Data and timestamped information. Furthermore, they address the ethical implications of data science, emphasizing the importance of understanding causality and avoiding common pitfalls like data leakage and overfitting.
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/Doing-Data-Science-Straight-Frontline/dp/1449358659?&linkCode=ll1&tag=cvthunderx-20&linkId=715be3f5715c3184388cb0f21448b7aa&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/Doing-Data-Science-Straight-Frontline/dp/1449358659?&linkCode=ll1&tag=cvthunderx-20&linkId=715be3f5715c3184388cb0f21448b7aa&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
2.2
55 ratings
offers an overview of data science, drawing from a book based on a university course. It explores various algorithms and models such as linear and logistic regression, Naive Bayes, k-means, and singular value decomposition, providing practical applications like spam filtering and recommendation engines. The sources also discuss essential concepts including exploratory data analysis, feature selection, data visualization, and the challenges of working with Big Data and timestamped information. Furthermore, they address the ethical implications of data science, emphasizing the importance of understanding causality and avoiding common pitfalls like data leakage and overfitting.
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/Doing-Data-Science-Straight-Frontline/dp/1449358659?&linkCode=ll1&tag=cvthunderx-20&linkId=715be3f5715c3184388cb0f21448b7aa&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/Doing-Data-Science-Straight-Frontline/dp/1449358659?&linkCode=ll1&tag=cvthunderx-20&linkId=715be3f5715c3184388cb0f21448b7aa&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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