Auto merge of #84 - abacon:readme-language, r=hobofan

docs/readme: fix some grammar issues in README.md

I've done a little proofreading of the README to correct some
small grammar issues and make it more readable.

Author: homu

README.md

@@ -8,7 +8,7 @@ Caffe, Rust and numerous research papers and brings modularity, performance and
 portability to deep learning. Leaf is lean and tries to introduce minimal
 technical debt to your stack.
 
-Leaf is a few months old, but thanks to its architecture and Rust already one of
+Leaf is a few months old, but thanks to its architecture and Rust, it is already one of
 the fastest Machine Intelligence Frameworks in the world.
 
 <div align="center">
@@ -22,16 +22,16 @@ machines without one. Run it with OpenCL or CUDA. Credit goes to
 [Collenchyma][collenchyma] and Rust.
 
 Leaf is part of the [Autumn][autumn] Machine Intelligence Platform, which is
-working on making AI algorithms 100x more computational efficient. Bringing
+working on making AI algorithms 100x more computational efficient. It seeks to bring
 real-time, offline AI to smartphones and embedded devices.
 
 We see Leaf as the core of constructing high-performance machine intelligence
-applications. Leafs' design makes it easy to publish independent modules to make
+applications. Leaf's design makes it easy to publish independent modules to make
 e.g. deep reinforcement learning, visualization and monitoring, network
 distribution, [automated preprocessing][cuticula] or scaleable production
 deployment easily accessible for everyone.
 
-For more info refer to,
+For more info, refer to
 * the [Leaf examples][leaf-examples],
 * the [Leaf Documentation][documentation],
 * the [Autumn Website][autumn] or
@@ -47,13 +47,13 @@ For more info refer to,
 [documentation]: http://autumnai.github.io/leaf
 
 > Disclaimer: Leaf is currently in an early stage of development.
-> If you are experiencing any bugs that are not due to not yet implemented
-> features, feel free to create a issue.
+> If you are experiencing any bugs with features that have been
+> implemented, feel free to create a issue.
 
 ## Getting Started
 
-If you are new to Rust you can install it as detailed [here][rust_download],
-and we recommend taking a look at the [official Getting Started Guide][rust_getting_started].
+If you are new to Rust you can install it as detailed [here][rust_download].
+We also recommend taking a look at the [official Getting Started Guide][rust_getting_started].
 
 If you're using Cargo, just add Leaf to your `Cargo.toml`:
 
@@ -94,7 +94,7 @@ others publish executable machine learning models build with Leaf. It features
 a CLI for easy usage and has a detailed guide in the [project
 README.md][leaf-examples].
 
-And Leaf comes with an examples directory as well, which features popular neural
+Leaf comes with an examples directory as well, which features popular neural
 networks (e.g. Alexnet, Overfeat, VGG). To run them on your machine, just follow
 the install guide, clone this repoistory and then run
 
@@ -107,7 +107,7 @@ cargo run --release --example benchmarks
 
 ## Ecosystem / Extensions
 
-We design Leaf and the other crates of the [Autumn Platform][autumn] as modular
+We designed Leaf and the other crates of the [Autumn Platform][autumn] to be as modular
 and extensible as possible. More helpful crates you can use with Leaf:
 
 - [**Cuticula**][cuticula]: Preprocessing Framework for Machine Learning
@@ -118,10 +118,10 @@ and extensible as possible. More helpful crates you can use with Leaf:
 
 ## Support / Contact
 
-- With a bit of luck you find us online on the #rust-machine-learing IRC at irc.mozilla.org,
+- With a bit of luck, you can find us online on the #rust-machine-learing IRC at irc.mozilla.org,
 - but we are always approachable on [Gitter/Leaf][gitter-leaf]
 - For bugs and feature request, you can create a [Github issue][leaf-issue]
-- And for more private matters, send us a mail straight to our inbox developers@autumnai.com.
+- For more private matters, send us email straight to our inbox: developers@autumnai.com
 - Refer to [Autumn][autumn] for more information
 
 [leaf-issue]: https://github.com/autumnai/leaf/issues
@@ -130,7 +130,7 @@ and extensible as possible. More helpful crates you can use with Leaf:
 
 Want to contribute? Awesome! We have [instructions to help you get started][contributing].
 
-Leaf has a near real-time collaboration culture and happens here on Github and
+Leaf has a near real-time collaboration culture, and it happens here on Github and
 on the [Leaf Gitter Channel][gitter-leaf].
 
 Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0
@@ -154,12 +154,12 @@ You can find the release history at the [CHANGELOG.md][changelog]. We are using
 
 #### _Why Rust?_
 
-The current hardware just recently became strong enough to support real-world
+Hardware has just recently become strong enough to support real-world
 usage of machine intelligence e.g. super-human image recognition, self-driving
-cars, etc.. For taking advantage of the computational power of the underlying
-hardware from GPUs to clusters you need a low-level language that allows for
+cars, etc. To take advantage of the computational power of the underlying
+hardware, from GPUs to clusters, you need a low-level language that allows for
 control of memory. But to make machine intelligence widely accessible you want
-to have a high-level comfortable abstraction over the underlying hardware.
+to have a high-level, comfortable abstraction over the underlying hardware.
 
 Rust allows us to cross this chasm.
 Rust promises performance like C/C++ but with safe memory-control. For now we
@@ -169,9 +169,9 @@ that will make large, parallel learning networks over CPUs and GPUs more
 feasible and more reliable to develop. The development of these future libraries
 is already under way e.g. [Glium][glium].
 
-On the usability side, Rust offers a trait-system, that makes it easy for
-researchers and hobbyists alike to extend and work with Leaf as if Leaf would
-have been written in a higher-level language such as Ruby, Python, Java, etc.
+On the usability side, Rust offers a trait-system that makes it easy for
+researchers and hobbyists alike to extend and work with Leaf as if it were
+written in a higher-level language such as Ruby, Python, or Java.
 
 #### _Who can use Leaf?_
 
@@ -184,14 +184,14 @@ developers alike.
 We believe strongly in machine intelligence and think that it will have a major
 impact on future innovations, products and our society. At Autumn, we experienced
 a lack of common and well engineered tools for machine learning and therefore
-started to create a modular toolbox for machine learning in Rust. We hope, that
-with making our work open source, we will speed-up research and development of
-production-ready applications and make their work easier as well.
+started to create a modular toolbox for machine learning in Rust. We hope that,
+by making our work open source, we will speed up research and development of
+production-ready applications and make that work easier as well.
 
 #### _Who is Autumn?_
 
 Autumn is a startup working on automated decision making. Autumn was started by
-two developers MJ and Max. The startup is located in Berlin and recently
+two developers, MJ and Max. The startup is located in Berlin and recently
 received a pre-seed investment from Axel Springer and Plug&Play.
 
 [glium]: https://github.com/tomaka/glium