20/20: Top 20 Programming Lessons I've Learned in 20 Years. This post could be viewed as hard lessons learned for newly graduated college students, entry-level programmers, or advanced developers who just want a chuckle.
I've been programming since I was 11 and I've loved technology and programming every since. There are some hard and easy lessons I've learned over time. As a fellow programmer, you may not have experienced these, but I'm offering them to individuals who are interested in learning more from my experiences. I'll be updating this as time goes on. Statistical Data Mining Tutorials.
The following links point to a set of tutorials on many aspects of statistical data mining, including the foundations of probability, the foundations of statistical data analysis, and most of the classic machine learning and data mining algorithms.
These include classification algorithms such as decision trees, neural nets, Bayesian classifiers, Support Vector Machines and cased-based (aka non-parametric) learning. They include regression algorithms such as multivariate polynomial regression, MARS, Locally Weighted Regression, GMDH and neural nets. And they include other data mining operations such as clustering (mixture models, k-means and hierarchical), Bayesian networks and Reinforcement Learning. I hope they're useful (and please let me know if they are, or if you have suggestions or error-corrections). Click here for a short list of topics. Everything you need to know about cryptography in 1 hour. Ottawa, ON Canada Cryptography is hard.
It usually takes many years of study before it is possible to make any serious contribution to the field; and even expert cryptographers often have flaws discovered in their work. However, merely using cryptography requires far less expertise. I like hardware.