Changes closing reminder and changes linewidth to appx. 80 characters

Author: quietlychris

new_contributor_guide.md

@@ -1,21 +1,55 @@
 ## Guide for New Contributors
 
-Hello, and welcome to the Rust-ML group! We're glad you may be interested in contributing to our efforts. First, please take the time to review our main README document, particularly around the "What do we do" section. 
-
-In general, the Rust-ML group emphasizes the Bazaar, not the Cathedral. In the [Zulip chat](https://rust-ml.zulipchat.com/), we regularly see people who say "Hi, I'm new here and would love to help contribute!" under the assumption that there may be a comprehensive Grand Plan that they can be directed towards. While well-intentioned, this approach is a little difficult to respond to because, while some individual projects do have roadmaps, the working group is not a Group with a Plan, but instead a collection of individuals working on things they're personally interested in. 
-
-We recommend you start by looking through the chat history in Zulip (particularly in the [#Code Review](https://rust-ml.zulipchat.com/#narrow/stream/237158-Code-Review) stream, which will have discussion of some of the more active projects) to see if there's something pre-existing that you might be interested in contributing to. Members of the Rust-ML team also help to maintain the site [arewelearningyet.com](https://www.arewelearningyet.com/), which has a more comprehensive list of crates and other projects in the Rust ecosystem. Alternatively, if you *don't* find something like that, write your own and share it with us! 
+Hello, and welcome to the Rust-ML group! We're glad you may be interested in 
+contributing to our efforts. First, please take the time to review our main [README](./README.md)
+document, particularly around the "What do we do" section. 
+
+In general, the Rust-ML group emphasizes the [Bazaar, not the Cathedral](https://en.wikipedia.org/wiki/The_Cathedral_and_the_Bazaar). In the 
+[Zulip chat](https://rust-ml.zulipchat.com/), we regularly see people who say "Hi, I'm new here and would love to 
+help contribute!" under the assumption that there may be a comprehensive Grand \
+Plan that they can be directed towards. While well-intentioned, this approach is 
+a little difficult to respond to because, although some individual projects do 
+have roadmaps, the working group is not a Group with a Plan, but instead a collection 
+of individuals working on things they're personally interested in. 
+
+We recommend you start by looking through the chat history in Zulip (particularly 
+in the [#Code Review](https://rust-ml.zulipchat.com/#narrow/stream/237158-Code-Review) stream, which will have discussion of some of the more active 
+projects) to see if there's something pre-existing that you might be interested in 
+contributing to. Members of the Rust-ML team also help to maintain the site 
+[arewelearningyet.com](https://www.arewelearningyet.com/), which has a more comprehensive list of crates and other 
+projects in the Rust ecosystem. Alternatively, if you *don't* find something like that, 
+write your own and share it with us! 
 
 ### Low Hanging Fruit
 
-One of the few projects that the Rust-ML group has direct ownership of and maintains is the [linfa](https://github.com/rust-ml/linfa/) classical machine learning meta-crate. It serves as a collection of multiple smaller algorithms in various domains. Although the implementations of the algorithms themselves usually exist and have some degree of testing, the crate as a whole can use some additional work in the areas of cross-language testing and benchmarking. [Luca Palmieri](https://github.com/LukeMathWalker), the original author of the linfa crate, did some great work on demonstrating the potential speed-ups of using Rust code for a k-means clustering algorithm by writing Rust->Python bindings and [comparing](https://www.lpalmieri.com/posts/2019-12-01-taking-ml-to-production-with-rust-a-25x-speedup/) the results against scikit-learn's implementation. 
-
-Creating a similar repository for each of linfa's sub-crates, or creating regression benchmarks for the sub-crates would be a great first contribution. Similarly, the documentation in terms of overall workflow for using Rust in a machine learning problem from scratch is somewhat limited. A Book [repository](https://github.com/rust-ml/book) has been created to help create a guide for newcomers, but is currently missing some content. Building a project using any of the crates in the ecosystem to solve a problem and clearly documenting that process would also be helpful to the community!
+One of the few projects that the Rust-ML group has direct ownership of and maintains
+is the [linfa](https://github.com/rust-ml/linfa/) classical machine learning meta-crate. It serves as a collection of multiple 
+smaller algorithms in various domains. Although the implementations of the algorithms
+themselves usually exist and have some degree of testing, the crate as a whole can 
+use some additional work in the areas of cross-language testing and benchmarking. 
+[Luca Palmieri](https://github.com/LukeMathWalker), the original author of the linfa crate, did some great work on demonstrating 
+the potential speed-ups of using Rust code for a k-means clustering algorithm by writing 
+Rust->Python bindings and [comparing](https://www.lpalmieri.com/posts/2019-12-01-taking-ml-to-production-with-rust-a-25x-speedup/) the results against scikit-learn's implementation. 
+
+Creating a similar repository for each of linfa's sub-crates, or creating regression 
+benchmarks for the sub-crates would be a great first contribution. Similarly, the 
+documentation in terms of overall workflow for using Rust in a machine learning 
+problem from scratch is somewhat limited. A Book [repository](https://github.com/rust-ml/book) has been created
+to help create a guide for newcomers, but is currently missing some content. 
+Building a project using any of the crates in the ecosystem to solve a problem and
+ clearly documenting that process would also be helpful to the community!
 
 ### A closing reminder
 
-Although some of the people who write code will lay out some sort of a larger roadmap or fill a leadership role to a degree, project management is rarely a full-time concern, especially for projects with a relatively low number of contributors. Therefore, it's usually best to approach things from a "code first, communicate after." That is, feel free to say hi, but unless you have demonstrated some degree of serious intent in the form of a pull request or well-written bug report, existing contributors may not be able to dedicate their limited time towards interacting with you. 
+Although some of the people who write code will lay out some sort of a larger 
+roadmap or fill a leadership role to a degree, project management is rarely a 
+full-time concern, especially for projects with a relatively low number of contributors. 
+Therefore, it's usually best to approach things from a "code first, communicate after." 
+As in all open source projects you will get a faster response for a well-written bug 
+report or pull request. Also sometimes people are busy with their life and can't 
+spend time on their side projects. Please respect that we're all human and have 
+limited time.
 
 ### Updated 
 
-Updated on 20201014
+Updated on 20201024