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Data Analysis And Visualization
The provided Book excerpts from "Data Analysis and Visualization" cover the fundamental concepts of probability and statistics. It begins by explaining the basics of probability and introduces various probability distributions like Bernoulli, Binomial, Poisson, and Normal distributions. The text further dives into Exploratory Data Analysis (EDA) techniques, focusing on visualizing and analyzing both univariate and multivariate data. It also covers correlation measures like covariance and Pearson's Correlation Coefficient. The text then moves into inferential statistics, explaining joint and conditional probabilities, as well as Bayesian inference. Finally, the text explores linear algebra concepts essential for machine learning, including vectors, matrices, transformations, and dimensionality reduction techniques like PCA and t-SNE.
You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cyber_security_summary
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
Discover our free courses in tech and cybersecurity, Start learning today:
https://linktr.ee/cybercode_academy
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By CyberSecurity Summary
2.2
55 ratings
The provided Book excerpts from "Data Analysis and Visualization" cover the fundamental concepts of probability and statistics. It begins by explaining the basics of probability and introduces various probability distributions like Bernoulli, Binomial, Poisson, and Normal distributions. The text further dives into Exploratory Data Analysis (EDA) techniques, focusing on visualizing and analyzing both univariate and multivariate data. It also covers correlation measures like covariance and Pearson's Correlation Coefficient. The text then moves into inferential statistics, explaining joint and conditional probabilities, as well as Bayesian inference. Finally, the text explores linear algebra concepts essential for machine learning, including vectors, matrices, transformations, and dimensionality reduction techniques like PCA and t-SNE.
You can listen and download our episodes for free on more than 10 different platforms:
https://linktr.ee/cyber_security_summary
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
Discover our free courses in tech and cybersecurity, Start learning today:
https://linktr.ee/cybercode_academy
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