Update README.md

Author: ujjwalkarn

README.md

@@ -14,12 +14,36 @@ This repo contains several Python tutorials for data analysis tasks.
     - [Scripting with Python](https://www.schrodinger.com//AcrobatFile.php?type=supportdocs&type2=&ident=404)
     - [**Can I use Python as a bash replacement?**](http://stackoverflow.com/questions/209470/can-i-use-python-as-a-bash-replacement)
 
-##ML with Python
+##Machine Learning with Python
 - [**AWESOME Python Machine Learning Book**](https://github.com/rasbt/python-machine-learning-book)
 - [Table of Contents and Code Notebooks](https://github.com/rasbt/python-machine-learning-book/blob/master/README.md#table-of-contents-and-code-notebooks)
 - [Machine Learning with scikit learn](http://www.dataschool.io/machine-learning-with-scikit-learn/)
 - [Cheatsheet](http://www.analyticsvidhya.com/blog/2015/09/full-cheatsheet-machine-learning-algorithms/)
 
+
+##scikit-learn
+- [Wiki](https://en.wikipedia.org/wiki/Scikit-learn)
+- [**Introduction to machine learning with scikit-learn**](https://github.com/justmarkham/scikit-learn-videos), [**Videos!**](http://blog.kaggle.com/author/kevin-markham/)
+- [**A Gentle Introduction to Scikit-Learn: A Python Machine Learning Library**](http://machinelearningmastery.com/a-gentle-introduction-to-scikit-learn-a-python-machine-learning-library/)
+- [**PyData Seattle 2015 Scikit-learn Tutorial**](https://github.com/jakevdp/sklearn_pydata2015), [sklearn_scipy2013](https://github.com/jakevdp/sklearn_scipy2013)
+- [SKLEARN BENCHMARKS: A centralized repository to report scikit-learn model performance across a variety of parameter settings and data sets.](https://github.com/rhiever/sklearn-benchmarks)
+- [**Code example to predict prices of Airbnb vacation rentals, using scikit-learn on Spark**](https://github.com/mapr-demos/spark-sklearn-airbnb-predict)
+- [**ML with scikit learn**](http://amueller.github.io/sklearn_tutorial/)
+- [Parallel and Large Scale Machine Learning with scikit-learn](https://speakerdeck.com/ogrisel/parallel-and-large-scale-machine-learning-with-scikit-learn), [Meetup](http://datasciencelondon.org/machine-learning-python-scikit-learn-ipython-dsldn-data-science-london-kaggle/)
+
+
+##Linear Regression
+- [Linear Regression in Python](http://nbviewer.ipython.org/github/justmarkham/DAT4/blob/master/notebooks/08_linear_regression.ipynb), [Blog Post](http://www.dataschool.io/linear-regression-in-python/)
+
+##Logistic Regression
+- [Logistic Regression with scikit learn](http://www.dataschool.io/logistic-regression-in-python-using-scikit-learn/)
+
+##Neural Networks
+- [Implementing a Neural Network from scratch](http://www.wildml.com/2015/09/implementing-a-neural-network-from-scratch/), [Code](https://github.com/dennybritz/nn-from-scratch)
+- [Speeding up your Neural Network with Theano and the gpu](http://www.wildml.com/2015/09/speeding-up-your-neural-network-with-theano-and-the-gpu/), [Code](https://github.com/dennybritz/nn-theano)
+- [Recurrent Neural Net Tutorial Part 1](http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-to-rnns/), [Part 2] (http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-2-implementing-a-language-model-rnn-with-python-numpy-and-theano/), [Code](https://github.com/dennybritz/rnn-tutorial-rnnlm/)
+
+
 ##Data Science with Python
 - [awesome-python](https://github.com/vinta/awesome-python)
 - [Pycon India 2015 Notes](http://www.analyticsvidhya.com/blog/2015/10/notes-impressions-experience-excitement-pycon-india-2015/)
@@ -40,16 +64,6 @@ This repo contains several Python tutorials for data analysis tasks.
 - [Timeseries analysis using Pandas](http://nbviewer.jupyter.org/github/twiecki/financial-analysis-python-tutorial/blob/master/1.%20Pandas%20Basics.ipynb)
 
 
-##scikit-learn
-- [Wiki](https://en.wikipedia.org/wiki/Scikit-learn)
-- [**Introduction to machine learning with scikit-learn**](https://github.com/justmarkham/scikit-learn-videos), [**Videos!**](http://blog.kaggle.com/author/kevin-markham/)
-- [**A Gentle Introduction to Scikit-Learn: A Python Machine Learning Library**](http://machinelearningmastery.com/a-gentle-introduction-to-scikit-learn-a-python-machine-learning-library/)
-- [**PyData Seattle 2015 Scikit-learn Tutorial**](https://github.com/jakevdp/sklearn_pydata2015), [sklearn_scipy2013](https://github.com/jakevdp/sklearn_scipy2013)
-- [SKLEARN BENCHMARKS: A centralized repository to report scikit-learn model performance across a variety of parameter settings and data sets.](https://github.com/rhiever/sklearn-benchmarks)
-- [**Code example to predict prices of Airbnb vacation rentals, using scikit-learn on Spark**](https://github.com/mapr-demos/spark-sklearn-airbnb-predict)
-- [**ML with scikit learn**](http://amueller.github.io/sklearn_tutorial/)
-- [Parallel and Large Scale Machine Learning with scikit-learn](https://speakerdeck.com/ogrisel/parallel-and-large-scale-machine-learning-with-scikit-learn), [Meetup](http://datasciencelondon.org/machine-learning-python-scikit-learn-ipython-dsldn-data-science-london-kaggle/)
-
 ##Text Mining
 - [**NLP with Python ORiley Book**](http://www.nltk.org/book_1ed/), [Python 3](http://www.nltk.org/book/)
 - [Text Analytics : Intro and Tokenization](http://a4analytics.blogspot.sg/2015/03/text-mining-post-1.html)
@@ -62,17 +76,6 @@ This repo contains several Python tutorials for data analysis tasks.
 - [Twitter-Sentiment-Analysis](https://github.com/ujjwalkarn/Twitter-Sentiment-Analysis)
 
 
-##Linear Regression
-- [Linear Regression in Python](http://nbviewer.ipython.org/github/justmarkham/DAT4/blob/master/notebooks/08_linear_regression.ipynb), [Blog Post](http://www.dataschool.io/linear-regression-in-python/)
-
-##Logistic Regression
-- [Logistic Regression with scikit learn](http://www.dataschool.io/logistic-regression-in-python-using-scikit-learn/)
-
-##Neural Networks
-- [Implementing a Neural Network from scratch](http://www.wildml.com/2015/09/implementing-a-neural-network-from-scratch/), [Code](https://github.com/dennybritz/nn-from-scratch)
-- [Speeding up your Neural Network with Theano and the gpu](http://www.wildml.com/2015/09/speeding-up-your-neural-network-with-theano-and-the-gpu/), [Code](https://github.com/dennybritz/nn-theano)
-- [Recurrent Neural Net Tutorial Part 1](http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-1-introduction-to-rnns/), [Part 2] (http://www.wildml.com/2015/09/recurrent-neural-networks-tutorial-part-2-implementing-a-language-model-rnn-with-python-numpy-and-theano/), [Code](https://github.com/dennybritz/rnn-tutorial-rnnlm/)
-
 ##Pickle
 - [Python serialization - Why pickle?](http://stackoverflow.com/questions/8968884/python-serialization-why-pickle)
 - [**Serializing Python Objects**](http://www.diveinto.org/python3/serializing.html), [**Binary Files**](http://www.diveinto.org/python3/files.html#binary)