Ali Unlu's repositories
Amazon-Kindle-recommendation-model
Create a sentiment model to identify the product features and recommendation trends
awesome-community-detection
A curated list of community detection research papers with implementations.
awesome-computational-social-science
A list of awesome resources for Computational Social Science
bank-customer-churn-analysis
The aim of this post is to predict the churn of bank customers.
best-of-ml-python
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
Comparative-Principal-Component-Analysis
In this analysis, I will demonstrate how PCA works in different tasks and how much time and resources we save in our daily analysis.
Comparison-of-Finnish-Sentiment-dictionaries
Sentiment analysis for the Finnish Language
Data-science
Collection of useful data science topics along with code and articles
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
EDA-Car-Dataset
In this analysis, I will demonstrate how to explore the cars dataset using Python. I will first load the dataset and then process the data. I will also visualize the dataset and then finally apply ttest to explore the relationship between variables.
group-projects
Learning materials
Hands-On-Explainable-AI-XAI-with-Python
Explainable AI with Python, published by Packt
K-Means-Cluster-Analysis
In this analysis, I will demonstrate how PCA and K-Means clustering can be applied to credit risk data. In this data set, we do not have a target variable, which leads us to build an unsupervised machine learning model.
machine-learning-book
Code Repository for Machine Learning with PyTorch and Scikit-Learn
Modern-Time-Series-Forecasting-with-Python
Modern Time Series Forecasting with Python, published by Packt
network-analysis
Course web page
Network-Analysis-Made-Simple
An introduction to network analysis and applied graph theory using Python and NetworkX
predicting-drug-use
Machine learning for social science
Predicting-game-sales-with-pyhton
The aim of this demonstration is to illustrate how regression models could be used to predict global game sales. I will use three regression models, including Lasso, Ridge and ElasticNet with cross validation tecnique.
Predicting-global-game-sales
Predicting global game sales with R
sentiment-analysis-with-tensorflow
In this project we will create and train a neural network model to classify movie reviews taken from IMDB as either a positive review or a negative review. Essentially, we want to create and train a neural network model which, given a text review, will be able to predict if the overall sentiment of the review is more negative or more positive.
Time-Series-Analysis-with-Facebook-Prophet
I previously analyzed the same data with SAMIRA to predict the future temperature for Istanbul. In this analysis, I will re-analyze the same topic with a different model. As known, fbprophet is provided by Facebook to predict the future trend. Prophet follows the sklearn model API.
Time-Series-Analysis-with-LSTM
I previously illustrated two forecasting implementations with the same data set. This is the last one in these series using deep learning model.
Time-series-analysis-with-SARIMA
In this demonstration, we make a time series analysis based on a temperature data set.
Travel-Customer-Churn-with-Oversampling
The aim of this post is to identify and visualize factors that contribute to customer churn of a travel company.