Template for crypto currency price prediction Mini Project.ppt

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1. Department of CSE(AI&ML)
Academic year: 2023-24
Mini Project (21AIMP67) –Review 1 Presentation
GUIDE:
Guide Name
Designation
Department of ISE
DBIT, Bengaluru
PROJECT TEAM:
1. Name (USN)
2. Name (USN)
3. Name (USN)
4. Name (USN)
Project Title

2. Contents
•Index
•Introduction
•Problem Statement
•Objectives
•prototype design/model
•progress of the work done with coding
•code execution
•out put discussion
•Conclusion
•References

3. INTRODUCTION
•Placementsareconsideredtobeveryimportantforeachandeverycollege.Thebasicsuccessofthe
collegeismeasuredbythecampusplacementofthestudents.
•Everystudenttakesadmissiontothecollegesbyseeingthepercentageofplacementsinthecollege.
Hence,inthisregardtheapproachisaboutthepredictingandrecommendingtheplacementnecessaryin
thecolleges.
•Theaimistodevelopaplacementpredictionandrecommendationsystemwhichpredictstheprobability
ofstudentgettingplacedandalsorecommendsthesuitablejobforparticularskillsofthestudent.
•Machinelearningalgorithmsareusedforpredictionandrecommendation.
•Decisiontree,LogisticRegression,RandomForestareusedtoclassifystudentsintoappropriateclusters
andtheresultwouldhelptheminimprovingtheirprofileandaccuracyofrespectedalgorithmsarenoted
andwiththecomparisonofvariousmachinelearningtechniques.
•Thiswouldhelpbothrecruitersaswellasstudentsduringplacementsandrelatedactivities.

4. PROBLEM STATEMENT
•Placementsareconsideredtobeveryimportantforeachandeverycollege.
•Everystudenttakesadmissiontothecollegesbyseeingthepercentageofplacementsinthecollege.
•Theaimistodevelopaplacementpredictionandrecommendationsystemwhichpredictstheprobability
ofstudentgettingplacedandalsorecommendsthesuitablejobforparticularskillsofthestudent.

5. •Itiseasytopredicttheplacementprobabilityofthestudents.
•Tominimizenumberofworkinghoursforthestaffoftrainingandplacementdepartment.
•ThismodelhasusedPlacementdatasetsfromonlinewebsitesorcollegeplacementdepartment.A
placementdatasetisusedtotrainthemodelandthenanotherunplacedstudent'sdatasetisusedfor
gettingtheresult.
•Whenthedataisconsidered,alwaysaverylargedatasetwithalargeno.ofrowsandcolumnswillbe
noted.
•Thedatasetincludestheacademicandprimaryskills.Thedatasetconsistsof1200individualdatasets
thatareconsideredfromthepreviousyearstudents.Theattributesaretakenintoconsideration.
•Machinelearningalgorithmssuchaslogisticregression,randomforestanddecisiontreeareusedin
predictionofplacementprobabilityofthestudent.
•Contentbasedfilteringisusedinrecommendationsystem,torecommendjobpositionsuitableforthe
studentbasedontheirprimaryskills.
OBJECTIVES

6. PROJECT DESIGN/MODEL
There are sequences of important general steps involved
1. Model
2. Data input
3. Processing of data
4. Prototype out put

7. SOFTWARE & HARDWARE
REQUIREMENTS

8. TOOLS USED FOR DEVELOPMENT

9. OUTCOME

10. CONCLUSION & FUTURE SCOPE

11. References / Bibliography
[1]SenthilKumarThangavel,DivyaBharathiP,AbijithSankar,InternationalConferenceonAdvance“DataMiningApproachfor
PredictingStudentandInstitution'sPlacementPercentage”,Professor.AshokMAssistantProfessorApoorvaA,2016
InternationalConferenceonComputationalSystemsandInformationSystemsforSustainableSolutions.
[2]“StudentPlacementAnalyzer:ARecommendationSystemUsingMachineLearning”,dComputingandCommunication
Systems(ICACCS-2017),Jan.06-07,2017,Coimbatore,INDIA.
[3]"APlacementPredictionSystemUsingK-NearestNeighborsClassifier",AnimeshGiri,MVigneshVBhagavath,Bysani
Pruthvi,NainiDubey,SecondInternationalConferenceonCognitiveComputingandInformationProcessing(CCIP),2018.
[4]"ClassResultPredictionusingMachineLearning",PushpaSK,AssociateProfessor,ManjunathTN,ProfessorandHead,
MrunalTV,AmartyaSingh,CSuhas,InternationalConferenceOnSmartTechnologyforSmartNation,2020
[5].Sheetal,M.B,Savita,Bakare.“PredictionofCampusPlacementwithDataMiningAlgorithm-FuzzylogicandKnearest
neighbor.”InternationalJournalofAdvancedResearchinComputerandCommunicationEngineering5.62019:309-312.
[6.]Sumitha,R.,E.S.Vinothkumar,andP.Scholar."PredictionofStudentsOutcomeUsingDataMiningTechniques."Int.J.Sci.
Eng.Appl.Sci2.6(2016):132-139,2022
[7]. Kavyag, pranithay, sanjanaa, sirishadg, mamathaa.” smart system for student placement prediction “. international journal
of advance research,ideasand innovations in technology.2454-132x,2021.