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University Institute of Engineering Department of Computer Science & Engineering

The document is an experiment report for a student named Kundan Sahni. It discusses using Google Colab and the Pycaret library to train and develop a classification model on a dataset, save and load the model, and make predictions on new data. However, the report is incomplete as it does not include any observations, screenshots of the simulation, or results and summary from the experiment.

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27 views8 pages

University Institute of Engineering Department of Computer Science & Engineering

The document is an experiment report for a student named Kundan Sahni. It discusses using Google Colab and the Pycaret library to train and develop a classification model on a dataset, save and load the model, and make predictions on new data. However, the report is incomplete as it does not include any observations, screenshots of the simulation, or results and summary from the experiment.

Uploaded by

ngupta.ara
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as PDF, TXT or read online on Scribd
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University Institute of Engineering

Department of Computer Science & Engineering

Experiment: 2.1

Student Name: KUNDAN SAHNI UID: 23BCS13169


Branch: Computer Science & Engineering Section/Group: 416(B)
Semester: 1st Sem.
Date of Performance:
Subject Name: DISRUPTIVE TECHNOLOGIES

Subject Code: 23ECH-102

1. Aim of the practical: Task: Train and develop classifier model, save and load it. Make
classification on a new dataset. You can refer “Pycaret” for classification dataset.

2. Tool Used: Google Colaboratory

3. Basic Concept/ Command Description: 1. Version() 2. get_data

4. Code: Task: Train and develop classifier model, save and load it. Make classification on a
new dataset. You can refer “Pycaret” for classification dataset.
University Institute of Engineering
Department of Computer Science & Engineering
University Institute of Engineering
Department of Computer Science & Engineering

5. Observations, Simulation Screen Shots and Discussions:


University Institute of Engineering
Department of Computer Science & Engineering
University Institute of Engineering
Department of Computer Science & Engineering
University Institute of Engineering
Department of Computer Science & Engineering

6. Result and Summary:


University Institute of Engineering
Department of Computer Science & Engineering

7. Additional Creative Inputs (If Any):

Learning outcomes (What I have learnt):

1. How to import Pycaret.

2.How to import get_data.

3.How to create confusion matrix.

4.I have learned to create dataset.


University Institute of Engineering
Department of Computer Science & Engineering

Evaluation Grid:

Sr. Parameters Marks Obtained Maximum Marks


No.
1. Student Performance 12
(Conduct of experiment)
2. Viva Voce 10
3. Submission of Work Sheet 8
(Record)
Signature of Faculty (with Date): Total Marks Obtained: 30

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