horse power


Data Science Simplified Part 6: Model Selection Methods

@machinelearnbot

In the last article of this series, we had discussed multivariate linear regression model. Fernando creates a model that estimates the price of the car based on five input parameters.


Data Science Simplified Part 9: Interactions and Limitations of Regression Models

#artificialintelligence

In the last few blog posts of this series discussed regression models at length. Fernando has built a multivariate regression model. What if there are relations between horsepower, engine size and width? Can these relationships be modeled? This blog post will address this question.


Data Science Simplified Part 6: Model Selection Methods

@machinelearnbot

In the last article of this series, we had discussed multivariate linear regression model. Fernando creates a model that estimates the price of the car based on five input parameters. Fernando indeed has a better model. Yet, he wanted to select the best set of variables for input. The idea of model selection method is intuitive.


The hidden horse power driving Machine Learning models

#artificialintelligence

Machine Learning is becoming the only real available method to perform many modern computational tasks in near real time. Machine Vision, speech recognition and natural language processing have all proved difficult to crack with out ML techniques. When it comes to hardware, the tasks themselves do not need a great deal of computational power; but training the machine does – not to mention an awful lot of data. In the machine learning world, the more data you have the more accurate your ML model can be. Of course the more data you have the longer the training process will take.