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Prithvi Singh

India **********

Updated on : 25-Aug-2023

Resume Headline

Java Development Intern @CodeClause || CodeKaze All India Rank - 1045 College Rank -2 || 4 at HackerRank || Java || Python || 2 at Codechef

Skill Set : Amazon Web Services (AWS), Core Java, Machine Learning

Prefered Job Type : : Full-Time, Remote

Employement Details

IBM Innovation Camp Intern

IBM · Internship
Oct 2021 - Dec 2021

 Learned about many Machine Learning & Data Science

technologies Developed "Home price prediction system " using Python and ML libraries. Learned about many Machine Learning & Data Science technologies Developed "Home price prediction system " using Python and ML libraries.

  • Skills: Machine Learning · Python (Programming Language) · Software Development · Computer Science · Data Science · Data Structures · Algorithms · Code Review

Java Developer

CodeClause
May 2023 - Jun 2023

 Remote

  • Skills: Core Java

IBM Project Based Internship

IBM · Internship
May 2022 - Jun 2022

 IBM project based internship on Data Analytics. In which our team make the "Movie recommendations System" which is based Machine Learning.
What’s required for this?

1. Data. ML systems need data, so find and import the essential libraries with movie datasets that already have global ratings.

2. Analysis. Create generic recommendations of top-rated movies from the existing dataset.

3. Personalization. Get personalized ratings by providing your own movie scores.

4. Strategy. Implement content-based or collaborative filtering strategy.

5. Combination. Combine recommendation lists to get a reasonable estimate across the ratings. The combined dataset of movie ratings can now be used for either filtering model.IBM project based internship on Data Analytics. In which our team make the "Movie recommendations System" which is based Machine Learning. What’s required for this? 1. Data. ML systems need data, so find and import the essential libraries with movie datasets that already have global ratings. 2. Analysis. Create generic recommendations of top-rated movies from the existing dataset. 3. Personalization. Get personalized ratings by providing your own movie scores. 4. Strategy. Implement content-based or collaborative filtering strategy. 5. Combination. Combine recommendation lists to get a reasonable estimate across the ratings. The combined dataset of movie ratings can now be used for either filtering model.

  • Skills: Machine Learning · Machine learning algorithm · Python (Programming Language) · Kaggle

Education Details

Graduation in Computer science and engineering

Bachelor of Technology - BTech From Dr. A.P.J. Abdul Kalam Technical University

Passout Year : 2021

Course Type : Full Time

Percentage/Grade : 80.8 % Marks of 100 Maximum


Profile Summary

 Self motivated and problem solver 

Personal Details

Full Name Prithvi Singh
Gender Male
Marital Status Single
Email ID **********
Mobile No. **********
Date of Birth **********
Languages Known
-
Nationality
India