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Statistics for Machine Learning: Implement Statistical methods used in Machine Learning using Python

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Manage episode 524289463 series 3683458
Content provided by CyberSecurity Summary. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by CyberSecurity Summary or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
An educational resource detailing statistical concepts foundational to machine learning, including descriptive statistics (mean, median, mode, and measures of dispersion), probability theory, and methods for parameter estimation and hypothesis testing. The book covers various analytical techniques such as ANOVA, regression models (linear, logistic, and regularized forms), and non-parametric statistics, often illustrating their practical application using Python libraries like Pandas and NumPy. The text also offers an overview of machine learning algorithms, including supervised and unsupervised methods, positioning statistics as the core discipline underpinning these advanced applications.
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/Statistics-Machine-Learning-Implement-Statistical/dp/9388511972?&linkCode=ll1&tag=cvthunderx-20&linkId=334106a284fd7b6360bf1aa51ed5b699&language=en_US&ref_=as_li_ss_tl
Discover our free courses in tech and cybersecurity, Start learning today:
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1001 episodes

Artwork
iconShare
 
Manage episode 524289463 series 3683458
Content provided by CyberSecurity Summary. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by CyberSecurity Summary or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
An educational resource detailing statistical concepts foundational to machine learning, including descriptive statistics (mean, median, mode, and measures of dispersion), probability theory, and methods for parameter estimation and hypothesis testing. The book covers various analytical techniques such as ANOVA, regression models (linear, logistic, and regularized forms), and non-parametric statistics, often illustrating their practical application using Python libraries like Pandas and NumPy. The text also offers an overview of machine learning algorithms, including supervised and unsupervised methods, positioning statistics as the core discipline underpinning these advanced applications.
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/Statistics-Machine-Learning-Implement-Statistical/dp/9388511972?&linkCode=ll1&tag=cvthunderx-20&linkId=334106a284fd7b6360bf1aa51ed5b699&language=en_US&ref_=as_li_ss_tl
Discover our free courses in tech and cybersecurity, Start learning today:
https://linktr.ee/cybercode_academy
  continue reading

1001 episodes

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