title: Beginner's resources/introductions to classification algorithms
body: <p>everybody. I am entirely new to the topic of classification algorithms, and need a few good pointers about where to start some "serious reading". I am right now in the process of finding out, whether machine learning and automated classification algorithms could be a worthwhile thing to add to some application of mine.</p>
  
  <p>I already scanned through <em>"How to Solve It: Modern heuristics"</em> by Z. Michalewicz and D. Fogel (in particular, the chapters about linear classifiers using neuronal networks), and on the practical side, I am currently looking through the <a href="http://www.cs.waikato.ac.nz/~ml/weka/" rel="noreferrer">WEKA toolkit</a> source code. My next (planned) step would be to dive into the realm of Bayesian classification algorithms.</p>
  
  <p>Unfortunately, I am lacking a serious theoretical foundation in this area (let alone, having used it in any way as of yet), so any hints at where to look next would be appreciated; in particular, a good introduction of available classification algorithms would be helpful. Being more a craftsman and less a theoretician, the more practical, the better...</p>
  
  <p>Hints, anyone?</p>