Singularity Container Setup for Jupyter Notebook

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Explores GPU architecture, multithreading, SIMD processors, and CUDA programming for parallel computing.

Exception Handling in Python

Covers exception handling in Python, including try, raise, except, else, and finally blocks, with examples.

GPUs: Multithreading and Architecture

Explores GPUs' architecture, multithreading, and their role in machine learning, discussing limitations and future trends.

Advanced Pandas Functions

Focuses on advanced pandas functions for data manipulation, exploration, and visualization with Python, emphasizing the importance of understanding and preparing data.

GPUs: Introduction to CUDA

Introduces the basics of GPUs, CUDA programming, and thread synchronization for parallel computing applications.

Rhythmic Generation Techniques

Covers rhythm generation techniques, including Markov models and hierarchical rhythm generation, with a focus on Nancarrow's Study 14.

Introduction to MATLAB and GNU Octave

Introduces MATLAB and GNU Octave, covering basic concepts, workspace, data types, matrices, installation, and practical usage.

Introduction to Python: Basics and Anaconda Setup

Covers the basics of Python programming and setting up Anaconda and Jupyter Notebook.

Numerical Methods for Physics: Iterative Solutions and Mesh Convergence

Explores finite differences for solving linear systems from PDEs iteratively, emphasizing convergence criteria and exercises on singularities.

Advanced Pandas Functions

Covers advanced functions of Pandas, focusing on filtering, labeling, and manipulating dataframes.