Pinned Repositories
Answering-Business-Questions-using-SQLite
This is a first guided project of SQL in dataquest, an online platform where you can learn data analysis and science. Guided project is a project where problems are provided and I try to solve them using what I have learned. In this project, I solved business questions using Sqlite3. A sample database I worked on is Chinook database. The Chinook database contains information about the artists, songs, and albums from the music shop, as well as information on the shop's employees, customers, and the customers purchases. This information is contained in eleven tables. The access to the database from here 4 tasks to do selecting albums to purchase from artsts analyzing employee's performance analyzing sales by country analyzing album purchases and individual tracks purchases.
article_20455_geopandas
bayse
Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy
data
Data and code behind the articles and graphics at FiveThirtyEight
Grokking-Deep-Learning
this repository accompanies the book "Grokking Deep Learning"
handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Happiness-Report-Analysis
Worked on 2017 Happiness Report Analysis in Python.
Pandas-Data-Science-Tasks
Set of real world data science tasks completed using the Python Pandas library
practical-statistics-for-data-scientists
Code repository for O'Reilly book
kodaigit's Repositories
kodaigit/bayse
kodaigit/SuGaR
[CVPR 2024] Official PyTorch implementation of SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering
kodaigit/article_20455_geopandas
kodaigit/r_pro_salary_years
kodaigit/Spoon-Knife
This repo is for demonstration purposes only.
kodaigit/data
Data and code behind the articles and graphics at FiveThirtyEight
kodaigit/Grokking-Deep-Learning
this repository accompanies the book "Grokking Deep Learning"
kodaigit/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
kodaigit/Predicting-the-stock-market-
In this project, we are going to predict a closing value of S&P500 index. The data set can be downloaded from here. This index is often considered as one of good representations of the U.S. stock market. As a note, This is a basic machine learning project and this should not be used for any purposes in practice.
kodaigit/Predicting-the-total-number-of-bike-rentals
In this project, I am going to predict the total number of bikes people rent in a given hour using Random Forests.
kodaigit/practical-statistics-for-data-scientists
Code repository for O'Reilly book
kodaigit/Predicting-House-Sale-Prices
In this project, I am going to create a multiple linear regression model which predicit house sale prices in the city of Ames, Iowa. The result is that average RMSE is $26344.835 with Kfold validation(k=5). In terms of R2 and adjusted R2, they are like below. They are calculated when I implement train/test validation R squared is about 0.8819061471098402 Adjusted R squared is about 0.8810503945526651
kodaigit/Spam-Fileter-Using-Naive-Bayes
In this project, we are going to build a spam filter for SMS messages, using Naive Bayes algorithm. Our goal is making the filter with more than 80% of accuracy.
kodaigit/Answering-Business-Questions-using-SQLite
This is a first guided project of SQL in dataquest, an online platform where you can learn data analysis and science. Guided project is a project where problems are provided and I try to solve them using what I have learned. In this project, I solved business questions using Sqlite3. A sample database I worked on is Chinook database. The Chinook database contains information about the artists, songs, and albums from the music shop, as well as information on the shop's employees, customers, and the customers purchases. This information is contained in eleven tables. The access to the database from here 4 tasks to do selecting albums to purchase from artsts analyzing employee's performance analyzing sales by country analyzing album purchases and individual tracks purchases.
kodaigit/Happiness-Report-Analysis
Worked on 2017 Happiness Report Analysis in Python.
kodaigit/pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
kodaigit/Pandas-Data-Science-Tasks
Set of real world data science tasks completed using the Python Pandas library
kodaigit/RTutorial
A Quick Introduction to R and RStudio
kodaigit/ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
kodaigit/Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy