IJNRD Research Journal

WhatsApp
Click Here

WhatsApp editor@ijnrd.org
IJNRD
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.76

Issue per Year : 12

Volume Published : 9

Issue Published : 95

Article Submitted :

Article Published :

Total Authors :

Total Reviewer :

Total Countries :

Indexing Partner

Join RMS/Earn 300

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: PREDICTING A SMALL CAP COMPANY GROWTH USING PYTHON LIBRARIES
Authors Name: Kandadi Thirupathi Reddy , Prof. G. Shankar Lingam
Download E-Certificate: Download
Author Reg. ID:
IJNRD_200731
Published Paper Id: IJNRD2306638
Published In: Volume 8 Issue 6, June-2023
DOI:
Abstract: ABSTRACT Predicting a small cap company growth is always a difficult task but by using some technology we can predict it successfully. First we need to collect data from various sources and create graphs for data then predict the stock growth according to the market to the market conditions and company performance. To predict the stock growth we need to use some algorithms like linear regression algorithm, support vector machine learning algorithm and naïve bayes algorithms. These three algorithms are important to analyses the stock growth in a successful way. To predict the stock growth we need to use python coding language. The pre defined algorithms and libraries are helps to analyses the stock growth in a easier way. In this journal we practically shown you the code of python and the successful execution images also.
Keywords: smallcap, prediction, regression algorithm, machine learning, google colab.
Cite Article: "PREDICTING A SMALL CAP COMPANY GROWTH USING PYTHON LIBRARIES", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 6, page no.g358-g372, June-2023, Available :http://www.ijnrd.org/papers/IJNRD2306638.pdf
Downloads: 000118759
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID:IJNRD2306638
Registration ID: 200731
Published In: Volume 8 Issue 6, June-2023
DOI (Digital Object Identifier):
Page No: g358-g372
Country: Ellanthakunta/Jammikunta, Telangana, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2306638
Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2306638
Share Article:
Share

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijnrd.org
Semantic Scholar Microsaoft Academic ORCID Zenodo
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX PUBLON
DRJI SSRN Scribd DocStoc

ISSN Details

ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI
How to Get DOI? DOI

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Social Media

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Join RMS/Earn 300

IJNRD