Artificial Intelligence for Quantum Machine Learning
Artificial Intelligence for Quantum Machine Learning: Build Smarter Algorithms Using QML and Explore the New Era of Intelligent Machines by Pit Hilda
English | May 2, 2025 | ISBN: B0F7FG2SQ7 | 710 pages | EPUB | 0.36 Mb
English | May 2, 2025 | ISBN: B0F7FG2SQ7 | 710 pages | EPUB | 0.36 Mb
Unlock the Future of Intelligence — Where AI Meets Quantum Computing
Are you ready to master the powerful intersection of two transformative technologies — Artificial Intelligence and Quantum Computing? Artificial Intelligence for Quantum Machine Learning is your definitive guide to building smarter, faster, and more advanced algorithms using cutting-edge QML techniques.
Written for beginners and forward-thinking professionals alike, this comprehensive book walks you step-by-step through the practical world of machine learning using Python, and gradually introduces quantum machine learning (QML) concepts that are revolutionizing industries from finance to healthcare and robotics.
Inside this hands-on guide, you’ll discover:
- Foundations of Machine Learning – Learn the core concepts of supervised, unsupervised, and reinforcement learning using real Python code and popular libraries like scikit-learn, TensorFlow, and PyTorch.
- Deep Learning Projects – Build powerful neural networks, dive into convolutional and recurrent architectures, and implement real-world projects such as image classification and text sentiment analysis.
- Natural Language Processing (NLP) – Explore transformers, BERT, and language models that power today’s most advanced AI applications.
- Reinforcement Learning & Game AI – Create intelligent agents with OpenAI Gym and Q-learning to simulate decision-making in real environments.
- Quantum Machine Learning (QML) – Understand the foundational principles of quantum computing and how they enhance classical AI models through parallelism and quantum data encoding.
- Model Deployment Mastery – Discover how to deploy your machine learning models using Flask, cloud platforms (AWS, Heroku, Google Cloud), and integrate them into real applications.
- Ethics and Explainability in AI – Explore responsible AI practices, transparency, and fairness in algorithmic decision-making.
Key Takeaways:
- Learn with real datasets and real code — no fluff, just results.
- Build a portfolio of deployable projects you can showcase.
- Understand how quantum computing is shaping the next frontier of artificial intelligence.
- Transition confidently from theory to practice in both classical and quantum machine learning.
Artificial Intelligence for Quantum Machine Learning is your launchpad into the intelligent machines of tomorrow.
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Thanks For Buying Premium From My Links For Support