Update logistic regression README.

Author: trekhleb

homemade/logistic_regression/README.md

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 # Logistic Regression
 
+## Jupyter Demos
+
+▶️ [Demo | Univariate Linear Regression](https://nbviewer.jupyter.org/github/trekhleb/homemade-machine-learning/blob/master/notebooks/linear_regression/univariate_linear_regression_demo.ipynb) - predict `country happiness` score by `economy GDP`
+
+▶️ [Demo | Multivariate Linear Regression](https://nbviewer.jupyter.org/github/trekhleb/homemade-machine-learning/blob/master/notebooks/linear_regression/multivariate_linear_regression_demo.ipynb) - predict `country happiness` score by `economy GDP` and `freedom index`
+
+▶️ [Demo | Non-linear Regression](https://nbviewer.jupyter.org/github/trekhleb/homemade-machine-learning/blob/master/notebooks/linear_regression/non_linear_regression_demo.ipynb) - use linear regression with _polynomial_ and _sinusoid_ features to predict non-linear dependencies.
+
+## Definition
+
 **Logistic regression** is the appropriate regression analysis to conduct when the dependent variable is dichotomous (binary). Like all regression analyses, the logistic regression is a predictive analysis. Logistic regression is used to describe data and to explain the relationship between one dependent binary variable and one or more nominal, ordinal, interval or ratio-level independent variables.
 
 Logistic Regression is used when the dependent variable (target) is categorical.