Yesterday, I delivered a short presentation on R support for Microsoft Azure Machine Learning at ManchesterR user meeting. Below is the PPT embedded from slide share.
When you train a machine learning algorithm it is very important that you choose right set of parameters. When you don’t understand the in-side out of that algorithm it might be very difficult to choose and fine tune the parameters. Even if you understand the algorithm well, it might be daunting to run different iteration of training and evaluate a model with different combination of parameters – consider Neural Networks.
Microsoft Azure Machine Learning comes with a handy option to address the same with a module called Sweep Parameters. This module takes an untrained model along with training and validation data set and generates optimum parameter settings with just clicks.
I think one of the coolest features of Azure Machine Learning is the ability to evaluate different algorithms and choose the right one with just few mouse clicks. The Evaluate Model makes it happen.
Official Documentation Page for the evaluate model can be found here.
Anyone can make sense of its output and decide on the right model provided one has basic understanding of the followings:
It will be not worthwhile if your website is not optimized very well for Search Engine. To be found in search engine like Google, Bing etc. with higher rank it is always recommended that website should be optimized with different kind of tricks and strategies. Here I am going to list down some optimization tricks to better optimize of a website.
On Page website optimization
This optimization generally done in the pages of the website, which reflects on search results. Before going to optimize your web page, it’s my suggestion that do a little bit of research on the current state of website or web pages. In this case Google webmaster and Bing webmaster might be very helpful tool.