-

 BCA cblu question paper 4th sem C++






Comments

Post a Comment

Popular posts from this blog

MLP Support Teacher for Grading

-
  # Step 1: Import libraries import pandas as pd from sklearn . feature_extraction . text import TfidfVectorizer from sklearn . tree import DecisionTreeClassifier from sklearn . model_selection import train_test_split from sklearn import tree import matplotlib . pyplot as plt # Step 2: Create a simple dataset (Question + Subject + Difficulty) data = { 'question' : [ "Explain photosynthesis" , "Define gravity" , "What is chemical bonding" , "Describe kinetic energy" , "Explain mitosis" , "What is quantum mechanics" , "Describe water cycle" , "Explain Ohm's Law" , "What are atoms made of" , "Explain the nervous system" ], 'subject' : [ "Biology" , "Physics" , "Chemistry" , "Physics" , "Biology...
Read more

COMBINATIONAL LOGIC CIRUITS-MULTIPLEXER AND DEMULTIPLEXER

-
Image
HELLO EVERYONE, WELCOME TO MY BLOG. TODAY I AM GOIN TO SHOW YOU SOME QUICK NOTES FOR YOUR VIVA,PRACTICALS AND EXAMS.                                                              TOPIC- MULTIPLEXER AND DEMULTIPLEXER     MULTIPLEXER-                                                                    INTRODUCTION                                                                A multiplexer, also known as a data selector, is a device that selects between several analog or digital input signals an...
Read more

MLP AI for Special Education

-
  # Step 1: Import necessary libraries import pandas as pd import numpy as np from sklearn . model_selection import train_test_split from sklearn . preprocessing import LabelEncoder , StandardScaler from sklearn . svm import SVC from sklearn . tree import DecisionTreeClassifier , plot_tree from sklearn . metrics import classification_report , confusion_matrix import matplotlib . pyplot as plt import seaborn as sns # Step 2: Create a sample dataset # Features: Attention Span, Response Time, Interaction Level, Comprehension Score data = { 'attention_span' : [ 20 , 50 , 15 , 45 , 10 , 55 , 12 , 48 , 25 , 60 ], # in minutes 'response_time' : [ 5 , 3 , 8 , 2 , 10 , 2 , 9 , 3 , 6 , 2 ], # in seconds 'interaction_level' : [ 1 , 3 , 1 , 4 , 1 , 4 , 2 , 5 , 2 , 5 ], # scale of 1-5 'comprehension_score' : [ 60 , 85 , 55 , 90 , 50 , 88 , 58 , 92 , 65 , 95 ], # out of 100 ...
Read more