Showing posts with label data mining. Show all posts
Showing posts with label data mining. Show all posts

Friday, November 25, 2011

Some great resources on the web covering Machine Learning, Data Mining, R, Python and other topics

These are just a few web resources around Python, R, machine learning, data mining, and some other technical topics I've come across. I will update this list as time permits. In the mean time..enjoy!!

Some Good R videos
A collection of talks given by Hadley Wickham @hadleywickham on R
Stanford OpenClassroom - a bunch of CS classes Stanford. Full Courses Short Videos
List of freely available programming books

KDNuggets - latest KD news
Khan Academy application of machine learning to assess student mastery
CMU Machine Learning course

Quick Python Facts
Invent Your Own Computer Games with Python

Courtesy of @jeremyphoward
Getting in Shape for the sport of Data Science

Courtesy of @hackingdata
UCB Intro to Data Science
A good list of Machine learning, Statistical computing related courses
A great video with Jeff Hammerbacher detailing the future of Big Data

Courtesy of @peteskomoroch
Hidden Videos Courses in Math, Science and Engineering
Updated List of Datasets and Video Lectures



Sunday, July 10, 2011

What I'm doing this Summer

The long summer is upon us and I'm taking the much needed break from school. Though I'm still keeping really busy. This is a rundown of some of the things I'll be doing / working on this summer.
  • I'm interning at a startup company in the employment science space @rezscore as a Data Scientist Intern, They employ statistical and scientific techniques to grade resumes and match them to job descriptions. The free resume grading service also offers suggestions on how you could make some improvements to your resume. I'm having to implement supervised and unsupervised machine learning and data mining algorithms to classify and score the resumes.  It's been a lot of fun. I'm doing most of my work in Python and use R, SQL, Excel and SAS as needed to clean and structure data. (I will blogging at length later about techniques and steps in the data cleaning / structuring process and other tips and trick  figured out along the way)
  • I will be attending Scipy 2011 in Austin, TX . I'm really looking forward to the conference as this is my first professional Python conference, and this will also give me the chance to reconnect with friends in Austin.
  • I an working on creating a student club at A&M from Fall 2011. The objective and vision of the organization will be to bring like-minded students together in a collaborative environment to work on interesting data science / Big Data problems. I'm tagging this, Project Timbuktu for now.  Jumping through administrative hoops, finding an advisor and securing funding for the organization will not be an easy task especially in the current climate where departments are slashing budgets and expenses. More on  Project Timbuktu later.
  • I will also be attending  PyTexas 2011. This is actually at the end of the summer / early September in College Station
  • I attended a startup lessons / Lean startup conference at Austin Tech Ranch (startup incubator) early in the summer. This was basically a day long telecast conference which featured several startup big hitters. More on this later.