Archives for Model Selection

25 Dec

How to use Hyperopt for Distributed Hyperparameter Optimisation?

Hyperopt is a tool for hyperparameter optimization. It helps in finding the best value over a set of possible arguments to a function that can be a scalar-valued stochastic function

12 Mar

Are Larger Models Better For Compression

Ram Sagar BERT Model

When OpenAI released its GPT model, it had 1.5 billion parameters and made it the biggest model back then. It was soon eclipsed by NVIDIA’s Megatron, which had 8 billion parameters. Last month Microsoft released the world’s largest language model Turing NLG that has 17 billion parameters. In terms of hardware, any model with more…

The post Are Larger Models Better For Compression appeared first on Analytics India Magazine.

13 Jun

Parameter Tuning With Grid Search: A Hands-On Introduction With Food Cost Prediction Data Science Hackathon

Amal Nair Developers Corner

Model selection and parameter tuning can be a headache at times. It’s not an easy task to pick the best algorithm given plenty of options and neither is it possible to try out every one of them to find the best one. It is always a good practice or says a necessary practice to try…

The post Parameter Tuning With Grid Search: A Hands-On Introduction With Food Cost Prediction Data Science Hackathon appeared first on Analytics India Magazine.

10 May

Model Selection With K-fold Cross Validation — A Walkthrough with MachineHack’s Food Cost Prediction Hackathon

Amal Nair K-Fold Cross-validation

A Data Scientist goes through a lot of data that needs to be cleaned, pre-processed, modelled and visualised. All these processes may not be as simple as it may sound. Out of all these processes, at least some Data Science experts may agree that modelling is one of the easiest to get around as long…

The post Model Selection With K-fold Cross Validation — A Walkthrough with MachineHack’s Food Cost Prediction Hackathon appeared first on Analytics India Magazine.