Approximate Counting algorithms are techniques that allow us to count a large number of events using a very small amount of memory. It was invented by Robert Morris in 1977 and was published through his paper Counting large number of events in small registers
Great post - One suggestion is use a larger number(1E6) and also use log scale to see demonstrate how well it scale in relative terms
```
plt.plot(np.log(np.array(range(MAX_COUNT))), [np.log(x[0] + 1) for x in items], label = "n")
plt.plot(np.log(np.array(range(MAX_COUNT))), [np.log(x[1] + 1) for x in items], label = "v")
```