In this blog, we will write about regularization. we will discuss its purpose and how it works.
If there is one thing that jeopardizes a perfect Neural Network that would be overfitting. Overfitting refers to situations where the model has fit the training data so well that the model captures the noise and random fluctuations.
I assume we already know about using a validation set and early stopping in order to prevent overfitting from happening. Unfortunately, I have to say that these approaches are not 100% reliable. There may be certain situations where the validation loss stays the same or…
There are so many different types of machine learning systems that it is useful to classify them into broad categories, based on the following criteria:
- Whether or not they are trained with human supervision (supervised, unsupervised, semi-supervised, and reinforcement learning)
- Whether or not they can learn incrementally on the fly (online versus batch learning)
- Whether they work by simply comparing new data points to known data points, or instead by detecting patterns in the training data and building a predictive model, much like scientists do (instance-based vs. Model-based learning)
These criteria are not exclusive; you can combine them in any…
For the simplicity of the article, I decided to make most of my examples on a simple regression model (one independent variable and the target variable). However, they can be applied to multiple linear regression model, and indeed can be expanded to other forms of general linear models with a single target variable ANOVA, ANCOVA, and independent samples t-tests.
To have a better model in this regard consistency and efficiency play a vital role, consider our estimation method as Ordinary Least Squares (OLS) as is usually the case.
Humankind has made very significant advances in science and technology. However, a large number of questions still remain unanswered.
The very last science that has been discovered by humankind is computer science. The world’s first computer science degree program, the Cambridge Diploma in Computer Science, began at the University of Cambridge computer laboratory in 1953. In the eyes of science, the last child, computer science, is changing the world rapidly. Not only this change is not a simple linear change that has a straight relationship with time but also it is an exponential one which means one change leads to…
