7TH SEM CSE MACHINE LEARNING LAB PROGRAMS | ALL IN ONE
Here you can get 7TH SEM CSE ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING LAB PROGRAMS code | VTU 7TH SEM | VTU CSE LABORATORY.
Sr.No | Lab Program Description | Details |
---|---|---|
1 | Implementation of A* Algorithm | Checkout |
2 | Implementation of AO* Algorithm | Checkout |
3 | 1. Implement and demonstrate the FIND-S algorithm for finding the most specific hypothesis based on a given set of training data samples. Read the training data from a . CSV file. | Checkout |
4 | Program 2. FOR A GIVEN SET OF TRAINING DATA EXAMPLES STORED IN A .CSV FILE, IMPLEMENT AND DEMONSTRATE THE CANDIDATE-ELIMINATION ALGORITHM TO OUTPUT A DESCRIPTION OF THE SET OF ALL HYPOTHESES CONSISTENT WITH THE TRAINING EXAMPLES | Checkout |
5 | Program -3] WRITE A PROGRAM TO DEMONSTRATE THE WORKING OF THE DECISION TREE BASED ID3 ALGORITHM. USE AN APPROPRIATE DATA SET FOR BUILDING THE DECISION TREE AND APPLY THIS KNOWLEDGE TO CLASSIFY A NEW SAMPLE. | Checkout |
6 | Program 4] BUILD AN ARTIFICIAL NEURAL NETWORK BY IMPLEMENTING THE BACKPROPAGATION ALGORITHM AND TEST THE SAME USING APPROPRIATE DATASETS. | Checkout |
7 | Program 5. WRITE A PROGRAM TO IMPLEMENT THE NAÏVE BAYESIAN CLASSIFIER FOR A SAMPLE TRAINING DATA SET STORED AS A .CSV FILE. COMPUTE THE ACCURACY OF THE CLASSIFIER, CONSIDERING FEW TEST DATA SETS. | Checkout |
8 | Program 6. ASSUMING A SET OF DOCUMENTS THAT NEED TO BE CLASSIFIED, USE THE NAÏVE BAYESIAN CLASSIFIER MODEL TO PERFORM THIS TASK. BUILT-IN JAVA CLASSES/API CAN BE USED TO WRITE THE PROGRAM. CALCULATE THE ACCURACY, PRECISION, AND RECALL FOR YOUR DATA SET. | Checkout |
9 | Program 7. WRITE A PROGRAM TO CONSTRUCT AN ABAYESIAN NETWORK CONSIDERING MEDICAL DATA. USE THIS MODEL TO DEMONSTRATE THE DIAGNOSIS OF HEART PATIENTS USING STANDARD HEART DISEASE DATA SET. YOU CAN USE JAVA/PYTHON ML LIBRARY CLASSES/API. | Checkout |
10 | Program 8. APPLY EM ALGORITHM TO CLUSTER A SET OF DATA STORED IN A .CSV FILE. USE THE SAME DATA SET FOR CLUSTERING USING K-MEANS ALGORITHM. COMPARE THE RESULTS OF THESE TWO ALGORITHMS AND COMMENT ON THE QUALITY OF CLUSTERING. YOU CAN ADD JAVA/PYTHON ML LIBRARY CLASSES/API IN THE PROGRAM. | Checkout |
11 | Program 9. WRITE A PROGRAM TO IMPLEMENT K-NEAREST NEIGHBOUR ALGORITHM TO CLASSIFY THE IRIS DATA SET. PRINT BOTH CORRECT AND WRONG PREDICTIONS. JAVA/PYTHON ML LIBRARY CLASSES CAN BE USED FOR THIS PROBLEM. | Checkout |
12 | Program 10. IMPLEMENT THE NON-PARAMETRIC LOCALLY WEIGHTED REGRESSION ALGORITHM IN ORDER TO FIT DATA POINTS. SELECT THE APPROPRIATE DATA SET FOR YOUR EXPERIMENT AND DRAW GRAPHS. | Checkout |
Thanks for sharing the list of machine learning lab programs for the 7th sem CSE students! This will definitely help me prepare for my courses this semester. Can you please provide more details on each program, such as the topics covered and the skills they teach? I would also appreciate any recommendations for supplementary resources or books to read.
Great resource! Thank you for sharing all these Machine Learning Lab programs in one place. I’m currently a 7th semester CSE student and find this post very helpful in my studies. Will definitely refer back to it often.