Update landing README.md (#296)

I made a few things more prominent and updated wording, so that it's more understandable what the project is about.
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Dilshod Tadjibaev 2023-04-12 14:29:59 -05:00 committed by GitHub
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[![Rust Version](https://img.shields.io/badge/Rust-1.65.0+-blue)](https://releases.rs/docs/1.65.0)
![license](https://shields.io/badge/license-MIT%2FApache--2.0-blue)
> This library aims to be a complete deep learning framework with extreme flexibility written in Rust.
> The goal would be to satisfy researchers as well as practitioners making it easier to experiment, train and deploy your models.
----
This library strives to serve as a comprehensive **deep learning framework**, offering exceptional flexibility and written in Rust. Our objective is to cater to both researchers and practitioners by simplifying the process of experimenting, training, and deploying models.
<div align="left">
*__Disclamer__* _Burn is currently in active development, and there will be breaking changes. While any resulting issues are likely to be easy to fix, there are no guarantees at this stage._
> *__Disclamer__* _Burn is currently in active development, and there will be breaking changes. While any resulting issues are likely to be easy to fix, there are no guarantees at this stage._
__Sections__
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## Features
* Flexible and intuitive custom neural network [module](#module) 🔥
* [Training](#learner) with full support for `metric`, `logging` and `checkpointing` 📈
* [Tensor](#tensor) crate with backends as pluging 🔧
* [Tch](https://github.com/burn-rs/burn/tree/main/burn-tch) backend with CPU/GPU support 🚀
* [NdArray](https://github.com/burn-rs/burn/tree/main/burn-ndarray) backend with [`no_std`](#no_std-support) support, running on any platform 👌
* [Autodiff](https://github.com/burn-rs/burn/tree/main/burn-autodiff) backend making any backend differentiable 🌟
* [Dataset](https://github.com/burn-rs/burn/tree/main/burn-dataset) crate with multiple utilities and sources 📚
* Customizable and user-friendly neural network [module](#module) 🔥
* Comprehensive [training](#learner) capabilities, including `metrics`, `logging`, and `checkpointing` 📈
* Versatile [Tensor](#tensor) crate with pluggable backends 🔧
* [Torch](https://github.com/burn-rs/burn/tree/main/burn-tch) backend offering CPU/GPU support 🚀
* [NdArray](https://github.com/burn-rs/burn/tree/main/burn-ndarray) backend featuring [`no_std`](#no_std-support) compatibility for any platform 👌
* [Autodiff](https://github.com/burn-rs/burn/tree/main/burn-autodiff) backend enabling differentiability for all backends 🌟
* [Dataset](https://github.com/burn-rs/burn/tree/main/burn-dataset) crate with a variety of utilities and sources 📚
## Get Started