ML crash course at BUE

This is a crash course in classical and quantum ML at the 3rd Summer School and Internship Programme at CTP BUE, Egypt.

Link to You Tube videos:

https://www.youtube.com/watch?v=Voaq3Fz6dc0&list=PLA4uYJ1jShPmbTydLHUOF4PBJdUs8DNvq&index=1

Folder Codes contains all the python notebook that used to create the matirals in the lectures.

Folder Animation contains the animation used in the slides and lost when it converted to pdf.

The course covers basics of classical and quantum machine learning methods as

• Lecture_1.pdf Overview about recent classical and quantum machine learning algorithms in HEP.
• Lecture_2.pdf Introduction to ML, linear and non-linear regression models.
• Lecture_3.pdf Ensemble learning, decision trees, boosted decision tress and random forest.
• Lecture_4.pdf Introduction to deep learning and feed forward deep neural network.
• Lecture_5.pdf Convolution based neural network for image recognition.
• Lecture_6.pdf Introduction to quantum machine learning, quantum gates, quantum feature map, data encoding and VQCs.