bootcamp_machine-learning
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42-AI
Day00/ex02 - Explain shortly what is Variance
- Day: 00
- Exercise: 02 - Variance
In order to avoid coding a function which wasn't understood, the purpose of some formula could be explained.
You must implement the following formula as a function:
$$ \sigma^2 = \frac{1}{m} \sum_{i = 1}^{m} (x_i - \frac{1}{m} \sum_{j = 1}^{m} x_j)^{2} $$
Maybe explain what is variance, why it is used (gaussian curve, std)?
The explanation can be: The variance is a statistical concept, as the mean. It characterizes the variabily or spread of the dataset. The bigger is the variance of a dataset, the more it is spread around the mean value.
But since the bootcamp has changed in the phase 2, the enhancement cannot be make.
