programming.dev

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programming.dev is a collection of programming communities and other topics relevant to software engineers, hackers, roboticists, hardware and software enthusiasts, and more.

The site is primarily english with some communities in other languages. We are connected to many other sites using the activitypub protocol that you can view posts from in the "all" tab while the "local" tab shows posts on our site.

🔗 Site with links to all relevant programming.dev sites

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ℹ️ We have a wiki site that communities can host documents on

⚖️ All users are expected to follow our Code of Conduct and the other various documents on our legal site

❤️ The site is run by a team of volunteers. If youre interested in donating to help fund things such as server costs you can do so here

💬 We have a microblog site aimed towards programmers available at https://bytes.programming.dev

🛠️ We have a forgejo instance for hosting git repositories relating to our site and the fediverse. If you have a project that relates and follows our Code of Conduct feel free to host it there and if you have ideas for things to improve our sites feel free to create issues in the relevant repositories. To go along with the instance we also have a site for sharing small code snippets that might be too small for their own repository.

🌲 We have a discord server and a matrix space for chatting with other members of the community. These are bridged to each other (so you can interact with people using matrix from discord and vice versa.

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founded 1 year ago

ADMINS

An Introduction to Statistical Learning (with Applications in R or Python) (www.statlearning.com)

submitted 9 months ago by ericjmorey to c/r_programming

0 comments fedilink

cross-posted from: https://programming.dev/post/6942085

Book (Free)

The resource on statistical methods recommended to me the most has been An Introduction to Statistical Learning (with Applications in R or Python) by Gareth James, Daniela Witten, Trevor Hastie, Rob Tibshirani, and Jonathan Taylor. Its free to download and has been kept up to date. (The latest edition is from 2022.)

Online Course (Free with optional payment for "Verified Track")

For those that prefer a structured online course StanfordOnline: Statistical Learning with R by Trevor Hastie and Robert Tibshirani uses An Introduction to Statistical Learning (with Applications in R) as the course textbook.

More In-Depth Book

Individuals with advanced training in the mathematical sciences may wish to use The Elements of Statistical Learning (Data Mining, Inference, and Prediction) by Trevor Hastie, Robert Tibshirani, and Jerome Friedman which provides a more comprehensive and detailed treatment of a wider range topics in statistical learning.

An Introduction to Statistical Learning (with Applications in R or Python) (www.statlearning.com)

submitted 9 months ago by ericjmorey to c/python

3 comments fedilink

cross-posted from: https://programming.dev/post/6942085

Book (Free)

The resource on statistical methods recommended to me the most has been An Introduction to Statistical Learning (with Applications in R or Python) by Gareth James, Daniela Witten, Trevor Hastie, Rob Tibshirani, and Jonathan Taylor. Its free to download and has been kept up to date. (The latest edition is from 2022.)

Online Course (Free with optional payment for "Verified Track")

For those that prefer a structured online course StanfordOnline: Statistical Learning with R by Trevor Hastie and Robert Tibshirani uses An Introduction to Statistical Learning (with Applications in R) as the course textbook.

More In-Depth Book

Individuals with advanced training in the mathematical sciences may wish to use The Elements of Statistical Learning (Data Mining, Inference, and Prediction) by Trevor Hastie, Robert Tibshirani, and Jerome Friedman which provides a more comprehensive and detailed treatment of a wider range topics in statistical learning.

An Introduction to Statistical Learning (with Applications in R or Python) (www.statlearning.com)

submitted 9 months ago* (last edited 9 months ago) by ericjmorey to c/machine_learning

1 comments fedilink

Book (Free)

The resource on statistical methods recommended to me the most has been An Introduction to Statistical Learning (with Applications in R or Python) by Gareth James, Daniela Witten, Trevor Hastie, Rob Tibshirani, and Jonathan Taylor. Its free to download and has been kept up to date. (The latest edition is from 2022.)

Online Course (Free with optional payment for "Verified Track")

For those that prefer a structured online course StanfordOnline: Statistical Learning with R by Trevor Hastie and Robert Tibshirani uses An Introduction to Statistical Learning (with Applications in R) as the course textbook.

More In-Depth Book

Individuals with advanced training in the mathematical sciences may wish to use The Elements of Statistical Learning (Data Mining, Inference, and Prediction) by Trevor Hastie, Robert Tibshirani, and Jerome Friedman which provides a more comprehensive and detailed treatment of a wider range topics in statistical learning.

An Introduction to Statistical Learning with Applications in Python (www.statlearning.com)

submitted 1 year ago by NorthBySouth to c/python

0 comments fedilink