Income Score

• Description: The project predicts the credit score of a client.
• Technologies Used: The notebooks use Random Forest Regressor and Random Forest Classifier.

Movies Recomendation

• Description: The project predicts the users’ film preferences based on their past choices and behavior.
• Technologies Used: The notebooks uses cosine_similarity.

Massive Open Online Course Analysis

• Description: Analysis to present data on course revenue, in order to know which Course has the highest revenue.
• Technologies Used: Notebooks use web scraping techniques to get data from websites. A Power Bi dashboard is presented to show results.

Hospitalization

• Description: Analysis of characteristics of patients with a certain type of disease who are hospitalized.
• Technologies Used: The notebooks use Decision Tree Classifier, Confusion matrix, Cross Validation.

Create Database Based on CSV and Excel Files

• Description: Script to create MySQL DB based on CSV or Excel files.
• Technologies Used: Python, Workbench.

Credit Card Fraud Detection

• Description: Explore the best model for credit card fraud detection.
• Technologies Used: Python, K Neighbors Classifier, SVC, Gaussian Naive Bayes, Decision Tree Classifier, Random Forest Classifier, XGB Classifier, LGBM Classifier, Gradient Boosting Classifier, Ada Boost Classifier, Logistic Regression.

Waiter Tips Prediction

• Description: This project is about waiters' tips prediction using machine learning models.
• Technologies Used: Python, Lineat Regression.

Future Sales Prediction

• Description: This project is about future sales prediction using machine learning models.
• Technologies Used: Python, Lineat Regression.

Cryptocurrency Price Prediction for the next 30 days

• Description: This project is about Cryptocurrency Price Prediction for the next 30 days using machine learning models.
• Technologies Used: Python, Time Series.

Stock Price Prediction with Long Short - Term Memory

• Description: This project is about stock price prediction with LSTM using machine learning models.
• Technologies Used: Python, Tensorflow, Keras, Sequential, LSTM, Dense.

Image Classification

• Description: This project is about image classification with neuronal networks.
• Technologies Used: Python, Tensorflow, Keras, Sequential, Dense.