Add datasets description.

data/README.md

@@ -2,7 +2,7 @@
 
 This is a list of datasets that are used for Jupyter Notebook demos in this repository.
 
-#### MNIST (Handwritten Digits)
+### MNIST (Handwritten Digits)
 
 > [mnist-demo.csv](mnist-demo.csv)
 
@@ -12,39 +12,39 @@ A sample of original MNIST dataset in a CSV format. Instead of using full datase
 
 Each row in the dataset consists of 785 values: the first value is the label (a number from 0 to 9) and the remaining 784 values (28x28 pixels image) are the pixel values (a number from 0 to 255).
 
-#### World Happiness Report 2017
+### World Happiness Report 2017
 
 > [world-happiness-report-2017.csv](world-happiness-report-2017.csv)
 
 _Source: [Kaggle](https://www.kaggle.com/unsdsn/world-happiness#2017.csv)_
 
 Happiness rank and scores by country, 2017.
 
-#### Iris Flowers
+### Iris Flowers
 
 > [iris.csv](iris.csv)
 
 _Source: [ics.uci.edu](http://archive.ics.uci.edu/ml/datasets/Iris)_
 
 Iris data set data set consists of several samples from each of three species of Iris (`Iris setosa`, `Iris virginica` and `Iris versicolor`). Four features were measured from each sample: the length and the width of the sepals and petals, in centimeters.
 
-#### NYC Taxi
+### NYC Taxi
 
 > [nyc_taxi.csv](nyc_taxi.csv)
 
 _Source: [Kaggle](https://www.kaggle.com/boltzmannbrain/nab)_
 
 Number of NYC taxi passengers, where the five anomalies occur during the NYC marathon, Thanksgiving, Christmas, New Years day, and a snow storm. The raw data is from the [NYC Taxi and Limousine Commission](http://www.nyc.gov/html/tlc/html/about/trip_record_data.shtml). The data file included here consists of aggregating the total number of taxi passengers into 30 minute buckets.
 
-#### Microchips Tests (Artificial)
+### Microchips Tests (Artificial)
 
 > [microchips-tests.csv](microchips-tests.csv)
 
 _Source: [Machine Learning at Coursera](https://www.coursera.org/learn/machine-learning)_
 
 Artificial dataset in which `param_1` and `param_2` produce non-linear decision boundary.
 
-#### Non-Linear Y(X) Dependency (Artificial)
+### Non-Linear Y(X) Dependency (Artificial)
 
 > [non-linear-regression-x-y.csv](non-linear-regression-x-y.csv)