Update README.md

Author: krzjoa

README.md

@@ -162,12 +162,19 @@
 * [Xfer](https://github.com/amzn/xfer) - Transfer Learning library for Deep Neural Networks. <img height="20" src="img/mxnet_big.png" alt="MXNet based">
 * [MXNet](https://github.com/ROCmSoftwarePlatform/mxnet) - HIP Port of MXNet. <img height="20" src="img/mxnet_big.png" alt="MXNet based"> <img height="20" src="img/amd_big.png" alt="Possible to run on AMD GPU">
 
-### Chainer
+### Others
+* [CNTK](https://github.com/Microsoft/CNTK) - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit.
+* [Neon](https://github.com/NervanaSystems/neon) - Intel® Nervana™ reference deep learning framework committed to best performance on all hardware.
+* [Tangent](https://github.com/google/tangent) - Source-to-Source Debuggable Derivatives in Pure Python.
+* [autograd](https://github.com/HIPS/autograd) - Efficiently computes derivatives of numpy code.
+* [Myia](https://github.com/mila-udem/myia) - Deep Learning framework (pre-alpha).
+* [nnabla](https://github.com/sony/nnabla) - Neural Network Libraries by Sony.
+* [Caffe](https://github.com/BVLC/caffe) - A fast open framework for deep learning.
+* [Caffe2](https://github.com/pytorch/pytorch/tree/master/caffe2) - A lightweight, modular, and scalable deep learning framework (now a part of PyTorch).
+* [hipCaffe](https://github.com/ROCmSoftwarePlatform/hipCaffe) - The HIP port of Caffe. <img height="20" src="img/amd_big.png" alt="Possible to run on AMD GPU">
 * [Chainer](https://github.com/chainer/chainer) - A flexible framework for neural networks.
 * [ChainerCV](https://github.com/chainer/chainercv) - A Library for Deep Learning in Computer Vision.
 * [ChainerMN](https://github.com/chainer/chainermn) - Scalable distributed deep learning with Chainer.
-
-### Theano
 **WARNING: Theano development has been stopped**
 * [Theano](https://github.com/Theano/Theano) - A Python library that allows you to define, optimize, and evaluate mathematical expressions.<img height="20" src="img/theano_big.png" alt="Theano compatible">
 * [Lasagne](https://github.com/Lasagne/Lasagne) - Lightweight library to build and train neural networks in Theano. <img height="20" src="img/theano_big.png" alt="Theano compatible">
@@ -177,17 +184,6 @@
 * [platoon](https://github.com/mila-udem/platoon) - Multi-GPU mini-framework for Theano. <img height="20" src="img/theano_big.png" alt="Theano compatible">
 * [Theano-MPI](https://github.com/uoguelph-mlrg/Theano-MPI) - MPI Parallel framework for training deep learning models built in Theano. <img height="20" src="img/theano_big.png" alt="Theano compatible">
 
-### Others
-* [CNTK](https://github.com/Microsoft/CNTK) - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit.
-* [Neon](https://github.com/NervanaSystems/neon) - Intel® Nervana™ reference deep learning framework committed to best performance on all hardware.
-* [Tangent](https://github.com/google/tangent) - Source-to-Source Debuggable Derivatives in Pure Python.
-* [autograd](https://github.com/HIPS/autograd) - Efficiently computes derivatives of numpy code.
-* [Myia](https://github.com/mila-udem/myia) - Deep Learning framework (pre-alpha).
-* [nnabla](https://github.com/sony/nnabla) - Neural Network Libraries by Sony.
-* [Caffe](https://github.com/BVLC/caffe) - A fast open framework for deep learning.
-* [Caffe2](https://github.com/pytorch/pytorch/tree/master/caffe2) - A lightweight, modular, and scalable deep learning framework (now a part of PyTorch).
-* [hipCaffe](https://github.com/ROCmSoftwarePlatform/hipCaffe) - The HIP port of Caffe. <img height="20" src="img/amd_big.png" alt="Possible to run on AMD GPU">
-
 ## Web Scraping
 * [BeautifulSoup](https://www.crummy.com/software/BeautifulSoup/bs4/doc/): The easiest library to scrape static websites for beginners
 * [Scrapy](https://scrapy.org/): Fast and extensible scraping library. Can write rules and create customized scraper without touching the coure