Introduction to MATLAB and Octave

Related lectures (26)

Page 2 of 3

Explores principal components, covariance, correlation, choice, and applications in data analysis.

Explores generalization in deep learning, covering model complexity, implicit bias, and the double descent phenomenon.

Introduces the CS-250 Algorithms course, covering its structure, objectives, and key topics in algorithmic problem-solving.

Explores RSA cryptography computational problems, finite fields construction, and computational challenges in RSA cryptography.

Discusses advanced analysis concepts, focusing on differential equations and timers in microcontrollers.

Introduces NumPy, focusing on array creation, manipulation, and its advantages for scientific computing.

Explores the Cauchy problem, emphasizing solution finding and verification processes.

Covers recursion, dynamic programming, and algorithm design using divide and conquer strategies.

Covers the Gradient Young Theorem in the calculus of variations, discussing proofs and applications.

Introduces NumPy and Matplotlib, essential tools for scientific computing and data visualization in Python.