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Hands-On Quantum Machine Learning with Python
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Delve into Quantum Machine Learning with Python, learning basics of quantum computing, creating parameterized circuits, and solving classification tasks using hybrid algorithms and quantum phenomena.

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Hands-On Quantum Machine Learning With Python is your comprehensive guide to get started with Quantum Machine Learning - the use of quantum computing for the computation of machine learning algorithms. In this course, you'll learn the basics of machine learning and quantum computing. You'll learn how to create parameterized quantum circuits and variational hybrid quantum-classical algorithms that solve classification tasks. Additionally, you’ll learn about quantum superposition, entanglement, and interference and how you can use it to solve problems intractable for classical computers.

Hands-On Quantum Machine Learning With Python is your comprehensive guide to get started with Quantum Machine Learning - the use...Show More

WHAT YOU'LL LEARN

Learn the basics of machine learning and quantum computing.

Learn how to create parameterized quantum circuits and variational hybrid quantum-classical algorithms that solve classification tasks.

Explore quantum superposition, entanglement, and interference, and how you can use these concepts to solve problems that have been intractable for classical computers.

Extend your knowledge and learn how to solve new problems.

Of course, you will do some math. Of course, you will cover a little physics.

Learn the basics of machine learning and quantum computing.

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Content

116 Lessons14 Quizzes1 Assessment

1.

Getting Started

5 Lessons

Learn how to use quantum computing principles to enhance machine learning methodologies.

Quantum Machine Learning—Beyond The Hype

Quantum Computing

The Case for Quantum Machine Learning

Quiz: Introduction to Quantum Machine Learning

2.

Binary Classification

13 Lessons

Solve challenges with binary classification through data preprocessing, evaluation metrics, and classifier visualization.

Getting and Looking at the Dataset

Data Preprocessing: Missing Values

Data Preprocessing: Identifiers

Data Preprocessing: Handling Text and Categorical Attributes

Data Preprocessing: 4- Feature Scaling

Data Preprocessing: Training and Testing

Classifier Evaluation

Classifier Measures

Unmask the Hypocrite Classifier

Visualization of Hypocrite Classifiers

Performance Evaluation of Hypocrite Classifier

Quiz: Binary Classification

3.

Qubit and Quantum States

10 Lessons

Work your way through the fundamentals and practical applications of qubits and quantum states.

Exploring the Quantum States

A Visual Exploration of the Qubit State

Bypassing the Normalization

Exploring the Observer Effect

Parameterized Quantum Circuit

Variational Hybrid Quantum Classical Algorithm

Implementing of Variational Hybrid Quantum Classical Algorithm

The Weighting Pre‐processing

Quiz: Qubit and Quantum States

4.

Probabilistic Binary Classifier

4 Lessons

Apply your skills to create probabilistic models using Naïve Bayes and Gaussian Naïve Bayes.

Towards Naïve Bayes

Gaussian Naïve Bayes

Quiz: Probabilistic Binary Classifier

5.

Working with Qubits

9 Lessons

Deepen your knowledge of qubits, superposition, quantum gates, and probability manipulation.

You Don't Need to Be a Mathematician

A Reimplementation of OR

The Measured Qubit

When to Differentiate State |0> From State |1>

Gamble with Quantum Computing

Probabilities and the Qubit States

Rotating the Qubit State

Quiz: Working with Qubits

6.

Working with Multiple Qubits

14 Lessons

See how quantum entanglement, CNOT gates, and probability manipulation transform quantum computing dynamics.

Hands-On Introduction to Quantum Entanglement

Implementing the CNOT gate

The Equation Einstein Could Not Believe

The Two Qubit States and Their Transformation

Calculating the Transformation Matrix

Quantum Programming for Non-mathematicians

Representing a Marginal Probability

Calculating Joint Probability

The Controlled RY Gate

Calculating Conditional Probability

Applying the Prior

Calculating the Posterior

Quiz: Working with Multiple Qubits

Create a Classical-Quantum KNN Classifier Using Qiskit

Project

7.

Quantum Naïve Bayes

6 Lessons

Master the Quantum Naïve Bayes classifier using pre-processing, quantum circuit, and post-processing techniques.

More on Naïve Bayes

Calculating the Posterior Probability

Post-processing

Quiz: Quantum Naïve Bayes

8.

Quantum Computing Is Different

7 Lessons

Break down the principles of quantum computing, its unique algorithms, and the pivotal quantum oracle.

The No-Cloning Theorem

How to Solve a Problem with Quantum Computing

Depicting the Transformation O-gate

Deutsch's Algorithm

The Quantum Oracle, Demystified

Magician-created Code

Quiz: Working with Multiple Qubits

9.

Quantum Bayesian Networks

7 Lessons

Unpack the core of building and implementing Quantum Bayesian Networks for complex probabilistic analyses.

Introduction to Quantum Bayesian Networks

Bayesian Networks

Composing Quantum Computing Controls

Circuit Implementation

Executing the Circuit

Quiz: Working with Multiple Qubits

10.

Bayesian Inference

10 Lessons

Master Bayesian inference with quantum networks to estimate probabilities and predict survival.

Introduction to Bayesian Inference

Estimating a Single Data Point

Calculating the log‐likelihood when ignoring the missing data

Estimating a Variable

Calculating the Probabilities Related to the Ticket Class

Calculating the Parameters

Calculating the Marginal Probability and Log-likelihood

Calculating New Parameters

Predict Survival

Quiz: Bayesian Inference

11.

The World Is Not a Disk

11 Lessons

Apply your skills to grasp qubit phases, Bloch sphere states, and quantum gate effects.

The Qubit Phase

Two Different Qubit States

The Different States in the Bloch Sphere

Visualizing the Invisible Qubit Phase

Multi-qubit Phase

The Controlled Z-gate

The Bloch Spheres of the State | +->

Quantum Amplitudes and Probabilities

Quiz: The World Is Not a Disk

12.

Working with the Qubit Phase

5 Lessons

Take a closer look at handling quantum states using Grover's Algorithm and amplitude amplification techniques.

Using Grover's Algorithm

Basic Amplitude Amplification

Two-qubit Amplification

The Two‐qubit Grover Searching |10>

Quiz: Working with the Qubit Phase

13.

Search for Relatives

6 Lessons

Tackle quantum methods to optimize relational data for passenger survival predictions.

The Convenience Function and Probabilities for Relatives

Turning the Problem into a Circuit

The Oracle and Amplifier Functions

The Search Algorithm

Multiple Results

Quiz: Searching for Relatives

14.

Sampling

5 Lessons

Test your understanding of various quantum sampling methods to estimate probabilities efficiently.

Forward Sampling

Bayesian Rejection Sampling

Quantum Rejection Sampling

The Amplifier Function

15.

Conclusion

1 Lessons

Get familiar with future trends in quantum machine learning and continue your learning journey.

16.

APPENDIX

3 Lessons

Walk through configuring environments for quantum machine learning with Python on different platforms.

Configuring Your Quantum Machine Learning Workstation

Configuring Ubuntu for Quantum Machine Learning with Python

How to Set Up JupyterLab for Quantum Computing on Windows

Quantum Machine Learning in Python

Assessment

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

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