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G H RAISONI COLLEGE OF ENGINEERING AND MANAGEMENT

(Approved by AICTE, New Delhi and Recognized by DTE, Maharashtra)

An Autonomous Institute & Affiliated to Rashtrasant Tukadoji Maharaj Nagpur University, Nagpur

Accredited by NAAC with A+ Grade

Department of Artificial Intelligence

Block C

2^nd Floor

Room No C-2-05

MACHINE LEARNING LAB

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Outline

About Laboratory
List of Major Equipment / Software-Hardware Configuration
Laboratory Course Outcome
List of Experiments
Details of Funded Laboratory/ Projects (if any)
Glimpses of Laboratory

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About Laboratory

Information about Laboratory: The aim of the Machine Learning Lab in the Artificial Intelligence department is to provide students with a dedicated and well-equipped space to seamlessly build, deploy, and operate machine learning solutions at scale. This lab will facilitate hands-on experience with cutting-edge tools and frameworks, enabling students to explore various algorithms and techniques. By fostering an environment of experimentation and collaboration, the lab aims to enhance students' practical skills, deepen their understanding of machine learning concepts, and prepare them for real-world challenges in the rapidly evolving field of artificial intelligence. The department is equipped with Machine Learning laboratory with an area of 68.37 SQM. which has been established with well equipped systems of latest hardware configuration and modern open source software technologies.

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List of Major Equipment / Software-Hardware Configuration

Sr. No.	EQUIPMENT	QUANTITY
1	COMPUTER (LENOVO DESKTOP with specification 12th Gen Intel(R) Core(TM) i5-12400 2.50 GHz, 8.00 GB Ram, 512 SSD)	22
2	CASSING & CUPING	--
3	COMPUTER TABLE	22
4	COMPUTER CHAIR	23
5	ELECTRIC FITTING	--

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Laboratory Course Outcome

Name of Subject:	MACHINE LEARNING
LABORATORY COURSE OUTCOME
CO1	Understand complexity of Machine Learning algorithms and their limitations
CO2	Understand modern notions in machine learning and computing
CO3	Be capable of confidently applying common Machine Learning algorithms in practice and implementing their own
CO4	Be capable of performing experiments in Machine Learning using real-world data

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List of Experiments

Sr. No.	Experiment List
1	Implement a program for Linear Regression
2	Implement a program for Decision Tree
3	Implement the concept of K-Nearest neighborhood Algorithm
4	Implement a program for Principle Component Analysis
5	Implement the concept of Logistic Regression
6	Implement the concept of Naïve Bayes Algorithm
7	Demonstrate use of Clustering: using k-means algorithm through python program
8	Implement the concept of SVM in Machine Learning
Open Ended Experiments
1	Exploring Virtual Lab