Show me monte carlo algorithm
Sure, here is an example of a Monte Carlo Algorithm in Python:

```python
import numpy as np
from random import uniform

def simulate(n):  # Simulate n Bernoulli trials with p = 0.5
    return [uniform(0, 1) for i in range(n)]

simulations = []  # Keep track of the simulation results
for _ in range(10000):  # Run 10000 simulations
    simulation = simulate(100)  # Generate 100 trials each time

    results = sum([1 if r == True else 0 for r in simulation]) / len(simulation)  # Calculate the average result
    simulations.append(results)  # Add the results to the list

    print("Simulation:", _, ":", round(results, 2))
```

This code uses the `sum()` function and the `np.random.choice()` function to generate a set of simulatedBernoulli trial outcomes, where each trial has a probability of success equal to `p = 0.5`. The simulation results are stored in a list called `simulations`, which can be used to display the progress of the simulation over time.

Note that this is just one possible implementation of the Monte Carlo Algorithm. There are many other ways to perform the same task, depending on your specific requirements and preferences. Additionally, you may want to modify the parameters such as `n` or `p` to get a more accurate estimate of the true mean.