A senior data scientist with interest in Bayesian methods, novel NN architectures and run-time optimization tricks in python. Specializing in time series forecasting particularly in the field of supply chain forecasting.
Beyond Time Complexity – NumPy, Pandas and vanilla python optimization tricks you must try
Beyond basic algorithmic considerations when writing our code, you would be surprised how easy it is to get more than 100X increase in efficiency with less than 30 minutes of work without even improving the time complexity.
Opening the black box – an interpretable neural network architecture
Neural networks don’t have to be black boxes, if you use creative designs and match the architecture to your specific needs, you can create a network as interpretable as linear regression, but without its linear constraints.