An overview of the relevant quantum machine learning frameworks

Do you want to get started with Quantum Machine Learning? Have a look at Hands-On Quantum Machine Learning With Python.

Image by author, Frank Zickert

In quantum machine learning, we aim to harness the phenomena of quantum mechanics to deliver a huge leap forward in the computation of machine learning algorithms.

Machine learning still is a relatively new technology. But in comparison to quantum computing, it is quite mature. A look at the landscape of frameworks makes this apparent.

When the success of deep neural networks ended the third AI winter around 2014, we saw plenty of frameworks compete for supremacy. Some names have almost…


Quantum machine learning promises to be disruptive

This post is part of the book: Hands-On Quantum Machine Learning With Python.

In the recent past, we have witnessed how algorithms learned to drive cars and beat world champions in chess and Go.

Image by author, Frank Zickert — www.pyqml.com

Machine learning is being applied to virtually every imaginable sector, from military to aerospace, from agriculture to manufacturing, and from finance to healthcare.

But machine learning algorithms have become increasingly hard to train. So when we look at the representation, current machine learning algorithms, such as the Generative Pre-trained Transformer 3 (GPT-3) network, published in 2020, come to mind. GPT-3 produces human-like text.

Training the GPT-3…


I learned Quantum Machine Learning the hard way. But there’s a better way

This post is part of the book: Hands-On Quantum Machine Learning With Python.

This is the hard way

I did not have the fortune to take a quantum computing class in college. Not to speak of a class in quantum machine learning. At the time, it wouldn’t have been much fun anyway. In the early 2000s, quantum computing was just about to take the step from a pure theory to be evaluated in research labs. It was a field for theoretical physicists and mathematicians.

At the time, I haven’t even heard about it. When I heard about quantum computing for the first time, I think…


Grover’s search algorithm is one of the first and most prominent examples to show how a quantum circuit can be magnitudes faster than a classical algorithm

This post is part of the book: Hands-On Quantum Machine Learning With Python.

In a previous post, we built a conceptual understanding of how the algorithm works. It follows a simple procedure. A quantum oracle inverts the amplitude of the searched state. Then, the diffuser flips all states about the mean amplitude, therefore, magnifying the searched state.

Image by author, Frank Zickert

We learned that we can use phases to amplify an amplitude. If we apply an HZH-sequence, it turns a qubit from state |0⟩ into state |1⟩.


Even if you’re not a mathematician or a physicist

The one thing you need to get started with quantum machine learning is not a degree in physics. It is a teacher able to explain it simply!

This is the aim of Hands-On Quantum Machine Learning with Python.

Quantum machine learning is the use of quantum computing to solve machine learning problems. It does sound a little bit like rocket science. It really is!

Rocket science is a widely-used phrase for something intellectually difficult. Something outside of the capabilities of the average Cletus.

Image by author, Frank Zickert, inspired by “The Simpsons”

But the sole fact you stumbled across this post lets me safely assume you bring the intellectual…


The importance of circuit identities

This post is part of the book: Hands-On Quantum Machine Learning With Python.

Grover’s search algorithm is one of the first and most prominent examples to show how a quantum circuit can be magnitudes faster than a classical algorithm.

In the previous post, we built a conceptual understanding of how the algorithm works. It follows a simple procedure. A quantum oracle inverts the amplitude of the searched state. Then, the diffuser flips all states about the mean amplitude, therefore, magnifying the searched state.

Image by author, Frank Zickert

Building up some Intuition is one thing. Translating this intuition into a working quantum circuit is a…


The Intuition Of Grover’s Algorithm

This post is part of the book: Hands-On Quantum Machine Learning With Python.

In many situations, we need to find one particular item in a set of many items. Unsurprisingly, searching algorithms are among the most prominent and useful algorithms in Computer Science.

Let’s imagine you need to call a famous quantum computing pioneer, Mr. Grover. You search a phone book for his number because you don’t have it yet. You open up the book in the middle and you see names with the starting letter L. For G is before L you take the first half of the book…


What I told you was true… from a certain point of view

This post is part of the book: Hands-On Quantum Machine Learning With Python.

Quantum entanglement is one of the astonishing characteristics of quantum mechanics. Two entangled particles share a state of superposition — no matter how far apart they are.

From a practical perspective, we can use entanglement to let one qubit control the state of another. For instance, the controlled NOT-gate (CNOT- or CX-gate) switches the amplitudes of a target qubit only if the control qubit is in state |1⟩. Nothing happens if the control qubit is in state |0⟩.

Such controlled quantum gates let us precisely manipulate a…


And learn how to tell the difference between the relative and the global phase

This post is part of the book: Hands-On Quantum Machine Learning With Python.

The phase of a qubit is the decisive factor when we work with amplitudes. Even though we can’t measure the phase directly, it is not invisible. Once, we can use our simulator to visualize it. Second, we can use math to describe it precisely.

When we look at the Bloch Sphere, states with a positive amplitude reside at the front-side of the X- and Z-axes.

Image by author, Frank Zickert

By contrast, states with a negative amplitude reside at the back-side of the Bloch Sphere.

Frank Zickert

I have been working as an IT professional for 17 years. I studied Information Systems Development and earned my PhD in 2012 at Goethe University of Frankfurt.

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