Add Neural Network Related Resource - Ng's tutorial

README.md

@@ -120,6 +120,7 @@ _OSDSM Specialization: [Web Scraping & Crawling](https://github.com/datasciencem
 * **Deep Learning (Neural Networks)**
  * Neural Networks [Andrej Karpathy / Python Walkthrough](http://karpathy.github.io/neuralnets/)
  * Neural Networks [U Toronto / Coursera](http://bit.ly/utoronto-neuralnets)
+ * Unsupervised Feature Learning and Deep Learning [Tutorial](http://deeplearning.stanford.edu/wiki/index.php/UFLDL_Tutorial) by Andrew Ng  
 
 * **Social Network & Graph Analysis**
  * Social and Economic Networks: Models and Analysis / [Stanford / Coursera](http://bit.ly/stanford-socialeconnetworks)

specializations.md

@@ -9,7 +9,7 @@ _[Note: I'm adding this section due to the overwhelming amount of input from new
 
 Packages
 * [mlpy](http://mlpy.sourceforge.net) Machine Learning Python
-* Machine Learning Toolkit [MILK](http://packages.python.org/milk/)
+* [MILK](http://packages.python.org/milk/) Machine Learning Toolkit 
 * [MDP](https://pypi.python.org/pypi/MDP) a collection of supervised and unsupervised learning algorithms
 * [pyBrain](http://pybrain.org/) modular Machine Learning Library for Python
 * [Caffe](http://caffe.berkeleyvision.org/) framework for convolutional neural network algorithms 
@@ -37,6 +37,7 @@ Packages
 #### Visualization
 
 * [D3.js Tutorial](https://www.dashingd3js.com/table-of-contents)
+* [Highcharts](http://www.highcharts.com/)
 
 #### Social Network Analysis
 

transcripts/Taiyuan-Zhang-2014.md

@@ -0,0 +1,33 @@
+Taiyuan Zhang
+-----------------------
+### Brief Intro
+Machine learning and data mining. Large-scale data processing.  
+
+### Education
+**Carnegie Mellon University**, Pittsburgh, PA     Dec. 2015(Expected)  
+Master of Computational Data Science(\textit{Analytic}), School of Computer Science  
+Selected Courses: Machine Learning, Search Engine, Cloud Computing, Multimedia DB \& Data Mining  
+
+**Tsinghua University**, Beijing, China  
+Bachelor of Computer Software, School of Software   
+
+### Experience
+1.  Internship@Hulu
+2.  Earliest member of A technology startup
+
+### Projects
+#### Multi-Task Recursive Neural Network(10701 Machine Learning Project)}    
+1.  Implemented parser to transform training data into sematic tree required by the algorithm  
+2.  Implemented and tuned stochastic gradient descent and multi-task learning (with \emph{Python, Scipy})  
+
+
+#### Twitter Data Analysis    
+1.  Implemented \emph{Extract-Transform-Load} of twitter data with AWS Streaming Map Reduce.   
+2.  Configured MySQL/Hbase to store and index needed data  
+3.  Implemented and optimized web service with \emph{Undertow} framework in Java  
+
+
+#### Non-negative Matrix Factorization based Transfer Learning  
+1.  Designed and implemented a program that can automatically download news documents with categories through RSS from major news websites  
+2.  Developed a program to automatically extract information from heterogeneous Chinese news webpages  
+3.  Designed and implemented a new transfer learning algorithm based on NMF. The algorithm achieves better results in different transfer learning datasets (including a text dataset collected as described above) than state-of-art common subspace learning methods