Sequence modelling is popularly done using Recurrent Neural network(RNN) or its advancements as gated RNNs or Long-short term memory(LSTM). Handling events sequentially hinders parallel processing and when sequences are too long, then the model could potentially forget long-range dependencies in the input or could mix positional content.

Dependency modelling without…

I know its Diwali time near by and You are excited

  • To color the night with fireworks
  • Lit Diyas to spread light
  • Enjoy the festive season

Let us consider an interesting game where you will get a chance to play with a candle and generate ways of reaching some outcome.

You are a computer programmer who like to solve real world problems with the help of coding knowledge. Amazingly you constructed something very meaningful and someone liked your code so much that she is ready to pay you for using your code.

Your code got popularised and slowly you had…

Pattern! Patterns! Patterns!

That’s what we are concerned about while running a Data Mining pipeline which helps to find patterns in the dataset collected. But are all patterns interesting. Well, not really. Interesting patterns are the one, which exhibit all or some of the properties mentioned below:-

  • Easily Understood
  • Valid…

The ultimate goal of machine learning techniques, is to predict the actual probability distribution of data generating process. Now this data generating process could be from any trivial or non-trivial probability distribution and it might not be significant to have any assumption looking at the samples/training data taken from population…

Any machine learning algorithm, generally involves components as Optimisation procedure, cost function, modelling technique and the most important is “Dataset to learn”. Its said that any ML algo performs as good as the dataset it is fed with.

Most of the time that is spent following “Knowledge discovery from data”…

Nikhil Verma

Knowledge shared is knowledge squared | My Portfolio

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