Machine Learning Practice Lectures
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.
Author(s): Andrew H. Fagg
NA Pages 
IBM PC Assembly Language Lecture Notes
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.
Author(s): NA
361 Pages
MIPS Assembly Language Programming by Robert Britton
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
109 Pages
Assembly Language Programming by Richard Pawson
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.
Author(s): Richard Pawson, Peter Higginson
79 Pages
Lecture Notes in Assembly Language
The contents include: Before we begin, First program, NASM syntax, Basic CPU instructions, Debugging with GDB, First program linked with a C library, FPU, File operations, MMX, SSE, RDTS, Inline assembler, Introduction,Registers, Memory.
Author(s): Piotr Fulma
252 Pages
Assembly Language Princeton University
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.
Author(s): Princeton University
57 Pages
Machine Learning Practice Lectures
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.
Author(s): Andrew H. Fagg
NA Pages
