The contents
include: High Level Languages, Machine Languages, Assembly Languages, Why Learn Assembly
Language, Why Learn ARM Assembly Lang, Von Neumann Architecture, Registers and RAM, ALU,
Instruction Format, Signed vs Unsigned, 32-bit Arithmetic, 8- and 16-bit Arithmetic, Loads
and Stores, Defining Data, Byte Order.
This lecture note covers
essential topics such as system architecture, assembly processes, DOS file
operations, debugging, and Intel 8088 CPU registers, the course emphasizes
hands-on learning with practical assignments. The content explores addressing
modes, ASCII representation, system calls, segments, logical instructions, and
graphics programming. These notes serve as a valuable resource for students
seeking proficiency in low-level programming and hardware interfacing on the IBM
PC.
This PDF book covers
the following topics related to MIPS Assembly Language Programming : The MIPS
Architecture, Pseudocode, Number Systems, PCSpim The MIPS Simulator, Algorithm
Development, Reentrant Functions, Exception Processing, A Pipelined
Implementation, Embedded Processors.
Author(s): Computer Science
Department, California State University, Chico, California
This page covers the following topics related to ARM
assembly language :ISA varieties, ARM assembly
basics, A simple program: Adding numbers, Another example: Hailstone sequence,
Another example: Adding digits, Summary of instructions so far, Condition codes,
Basic memory instructions, Addressing modes, Initializing memory,
Multiple-register memory instructions.
This PDF covers the following topics related to Assembly Language
Programming : Fundamentals of assembly language, Introduction to assembly
language and ARMlite, Countdown, Matchsticks, Hangman, Indirect & Indexed
addressing, The System Stack, and Subroutines, Interrupts, Snake.
This lecture note
covers the following topics: Server Configuration, Python Overview, Pandas and
Numpy, Classifiers, Regression, Cross-Validation, Logistic Regression, Support
Vector Machines, Decision Trees, Ensemble Methods, Principal Component Analysis,
Embedding Methods, Clustering, Semi-Supervised Learning.