Predictive Analytics

Trying to predict which species are most threatened with extinction in the near future.

Imbalanced Classes, Resampling techniques, filling null value, Date,Time, Alphanumeric data

Multiple linear regression model implementation with automated backward elimination (with p-value and adjusted r-squared) in Python and R for showing the relationship among profit and types of expenditures and the states.

A collection of essential machine learning algorithms implemented from scratch and with libraries. Ideal for students and beginners to understand core ML concepts through hands-on examples.

Apply unsupervised learning techniques to identify customers segments.

scikit_learn

Embedding

Car Price Prediction

OneHotEncoder : Kategorik verileri "binary" (0 ve 1) sütunlarına ayırır. Her benzersiz kategori için ayrı bir sütun oluşturur. Özellikle sıralı olmayan kategorik değişkenler için uygundur.

Data cleaning tools, handling missing data, categorical data, feature scaling

Predict employee attrition using LogisticRegression and RandomForestClassifier.

This project predicts whether a person survived the Titanic disaster based on various features using machine learning. It utilizes pipelines, ColumnTransformer, and model serialization for efficient processing and prediction.

Loan approval prediction system using ML pipelines and Gradio, deployed on Hugging Face Spaces.

This is the Traffic Analysis and Prediction based project from RandomForest Classifier.

Create a binary classification model using a deep neural network

This project presents a comprehensive car price prediction model using machine learning techniques. The dataset is carefully explored and preprocessed, including handling missing values, encoding categorical features, and scaling numerical data. Visualizations are provided to understand key relationships and trends in car features and prices.

Machine learning and neural networks used to create a binary classifier capable of predicting whether applicants will be successful if funded by Alphabet Soup.

To predict whether a user will click on ad or not.