Skip to content

connectkishan1/Projects

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

39 Commits
 
 
 
 
 
 

Repository files navigation

Data Science Portfolio

This portfolio consists of several projects illustrating the work I have done in order to further develop my data science skills.

Table of Contents

Project Tags
Titanic: Machine Learning from Disaster
House Prices Prediction-Ames Housing dataset
Traffic-Sign-Board-Recognition
American Sign Language-Recognition
Digit Recognizer-Recognition_MNIST
House Prices Prediction-BOSTON Housing Dataset
Iris-Classifier-WebApp

Projects

  • Project for the kaggle competitions
  • Participation of the kaggle competition Titanic: Machine Learning from Disaster
  • We were graded on leaderboard scores and I scored 7th of the class with position 1266th of the leaderboard
  • I used a weighted average of Logistic regression, Random forest & SVM.
  • The focus of this project was mostly on feature engineering


Kaggle

  • Project for the kaggle competitions
  • Participation of the kaggle competition House Prices: Advanced Regression Techniques
  • We were graded on leaderboard scores and I scored 11th of the class with position 526th of the leaderboard
  • I used a weighted average of XGBoost, Lasso, ElasticNet, and Gradient Boosting Regressor
  • The focus of this project was mostly on feature engineering


  • Project for the course Deep Learning
  • I used CNN
  • using flow from directory
  • The focus of this project was mostly on Layers.

  • Project for the image Classification
  • I used CNN
  • using flow from directory
  • The focus of this project was mostly on .

  • Project for the course Deep Learning
  • I used CNN
  • Data Scource: Keras.Datasets
  • The focus of this project was mostly on Layers.

  • Project for the course Machine Learning
  • I used a weighted average of Linear regression.
  • The focus of this project was mostly on feature engineering

  • Project for the course Machine Learning
  • My First Classification Project
  • I used Logistic regression, Random forest & SVM.