This week, I have three different things to talk about.
First, my weekly story presents a brief tutorial on Quantum A or B. It is the result of a question I received.
Suppose you have two random events, A and B. A occurs with a probability of 40%, and B with a probability of 60%. So, we can say p(A) = 40% and p(B) = 60%. Moreover, both events co-occur with a probability of 20%. Thus p(A AND B) = 20%. As a result, the probability of either event must be 80% (p(A OR B) = 80%).
But how do we model this in a quantum circuit in Qiskit — IBM’s quantum development kit?
Second, I will discuss how quantum computing can be integrated with machine learning to develop algorithms to solve real-world problems.
Third, the printed versions of my brand-new book’s Kickstarter campaign Hands-On Quantum Machine Learning With Python Volume 2: Combinatorial Optimization, were shipped last week! Some of you already have your copy in your hands.
For all who did not have the chance to back up the Kickstarter, don’t worry. You can still get the eBook and also the printed version.