#QuantumComputing #QuantumMachineLearning #QSVM Join @JonKrohnLearns and Dr. Amira Abbas, Quantum Computing Researcher at the University of Amsterdam, as we journey through the intricacies of qubits, the methodical processes of Quantum ML, and the vast potential of Quantum Support Vector Machines. For anyone aiming to harness the power of quantum computing in machine learning, Amira provides noteworthy ML tools suggestions to kickstart your journey. Whether you're a seasoned tech enthusiast or newly curious about the advances in computing, this episode promises a blend of in-depth exploration and actionable insights. This episode is brought to you by Gurobi (https://gurobi.com/sds), the Decision Intelligence Leader, by ODSC (https://odsc.com), the Open Data Science Conference, and by CloudWolf (https://www.cloudwolf.com/sds), the Cloud Skills platform. Interested in sponsoring a SuperDataScience Podcast episode? Visit https://jonkrohn.com/podcast for sponsorship information. In this episode you will learn: • [00:00:00] Introduction • [00:02:06] Quantum computing vs classical computing • [00:10:11] What is quantum entanglement • [00:13:32] What is a qubit • [00:28:34] The best problems for quantum ML • [00:37:32] Three distinct steps in quantum ML and its potential • [00:47:27] Quantum neural networks • [01:08:47] What Amira's working on at the moment • [01:19:26] How to get started in quantum ML • [01:28:59] Amira's recommended ML tools for quantum computing Additional materials: https://www.superdatascience.com/721