Meghnath's repositories
Concrete-Compressive-Strength-Prediction
Different modeling techniques like multiple linear regression, decision tree, and random forest, etc. will be used for predicting the concrete compressive strength. A comparative analysis will be performed to identify the best model for our prediction in terms of accuracy. The best model will be helpful for civil engineers in choosing the appropriate concrete for bridges, houses construction.
COVID19-dataset-C-
Perform different operations on the COVID19 dataset using the C++ OOPS concept.
Warehouse-Retailer-Seller-Gurobi-Network-flow
Network optimization problem solved using Gurobi Python
A-PATIENT-ASSISTANT-NETWORK-DATABASE-SYSTEM
The Patient Assistance Network (PAN) is a non-profit organization that provides support and care for patients. PAN needs to implement a database system to keep track of the personnel necessary to support the organization. In this project the task will be to design and implement database system using SQL, JAVA and JSP.
Network_Optimization_Gurobi-Python
4 sample solutions on Network optimization problems.
Project-Portfolio
List of Project descriptions in detail
Analysis-on-Employee-data.txt-using-Python
Data-interpretation using Python matplotlib, seaborn libraries
Data-Visualization-on-Titanic-survivors-data
Data visualization using Python matplot, seaborn libraries.
Python_basic
Reading text file, Salary calculation, Lucky Seven Problem, Gottfried Leibniz
R-Sales-Prediction
Data wrangling, regression modeling and analysis.
SQL-Transact-JDBC
Learning objectives:
R-Basic-operations
Code implements:Use of Vectors, Introductory data exploration, Manipulating data in data frames
R-Data-Understanding
Data Understanding using- PCA, LDA, tSNE, and UMAP.
R-Exploratory-Data-Analysis
Learn the basic features of ggplot, plot advance density plots, explore different data visualization methods in R, explore missing values in data, ANOVA, and more.
Sorting-C-
Code to implement Quicksort, Bubble sort and Shell sort using C++
Statistics_Python
Python_stat module without using inbuilt libraries