Itachi Uchiha's repositories
COVID-19-Project
Done EDA for India as well as for World using the data which we have collected through API's
Machine-learning-projects
This includes projects of Supervised : such as Regression - SLR , MLR ,Classification - SVM , Log Reg , Dec Tree , KNN and Unsupervised : K Means , Heirarchical & DBSCAN & aslo recommendor systems
Twitter-Senttiment-Analysis
Hyper parameter tuning is applied for XGBOOST
Courses-
Quiz & Assignment of Coursera
Machine-learning-stanford-coursera
Matlab assignments and projects
EXCEL-CAPSTONE-PROJECT-PUBG
Data Visualizations
Bank-Marketing-Using-Random-Forest-and-Logistic-Regression
Analyzed the bank data , formed visualizations using seaborn , Built a model based on selected features which we got from OLS , RFE and VIF . And made predictions using Logistic and random forest algorithms.
News-Category-Prediction-NLP-Random-Forest
Considering a news article & examined for the reliable and accurate prediction. To build a model for predicting the category of news used NLP cleaning techniques & then applied three algorithms.
Autombile-CAR-PRICE-PREDICTION-
Used Machine learning to predict the price of a car based on several characteristics. The objective is to build a model to understand the factors that drive the car of the price. This will help the automobile company launch their new car in the market effectively by pricing it better. Tasks performed : - Performed EDA on the data - Performed data cleanup as required - Picked the best variable for making a simple linear regression model - Perform train test split - Build model using best variable and report the R2 - Prepared a multiple regression model >> Applied feature selection approaches such as Variance Inflation Factor(VIF) , Ordinary Least Squares (OLS) and Recursive Feature elimination(RFE). - Final model is formed in a interpretable form
Student-Placement-Prediction-using-DECISION-TREE--
t takes data which contains Student data such as CGPA,No. of backlogs, Technical skills, Communicaton skills and forms a predictive model , which is further used to predict whether a student can be placed or not.Based on this prediction teachers can take care of students who are predicted as 0.With this a student increase his increase performance and prepare accordingly.
PUBG-Data-analysis
Updated 2 minutes ago PLAYER UNKNOWN BATTLEGROUNDS: This includes a pubg dataset which I have taken from kaggle and performed plotting functions. Impressive ! Get in zone and get down !
Boston-data-with-LINEAR-REGRESSION
Boston data with LINEAR REGRESSION