Very basic introduction to quantum computing given at Indaba Malawi 2022. Overviews some basic hardware in classical and quantum computing, as well as a few quantum machine learning algorithms in use today. Resources for self-study provided.
3. Machine Learning
Algorithms trained on data that are
useful in solving lots of problems in
industry:
Translating speech to text in
another language
Prediction of customer churn
Segmentation of customer bases
Forecasting crop yield
Predicting professional contacts
not in one’s network
7. Particle-based qubit with physical
circuit
Superposition of binary bit states
Rotation gates inducing non-
binary values
Many more types of circuits to
manipulate qubit
9. • Faster solutions to combinatorics
problems (including many graph
algorithms)
• Possible solutions where classical
computing takes too long to ever
compute
Massively
parallel
optimization
through
superposed
states
• Usually by finding good quantum
operators and circuit design
• Improves performance and speed
of deep learning algorithms
Learning
efficiency