This is a Mini-Project for CZ1115 (Introduction to Data Science and Artificial Intelligence) which focuses on movies from The Movie Database APIs. For detailed walkthrough, please view the source code in order from:

1. Data Extraction
2. Data Visualization
3. Data Resampling and Splitting
4. Logistic Regression
5. Neural Network

• @nicklimmm - Neural Networks, Data Resampling, Data Extraction
• @TCaken - Logistic Regression
• @coolcoolwhat - Data Visualization, Data Extraction

• Are we able to predict if a movie is good (rating above 7.2) based on its attributes?
• Which model would be the best to predict it?

1. Logistic Regression
2. Neural Networks

• Popularity and budget have low linear correlation value with ratings (watch out for bandwagons 🤣)
• Popularity of the casts and crews have higher linear correlation value with ratings
• Resampling imbalanced data improved model performance especially on the minority class
• Logistic Regression did not perform well with non-linearly correlated variables
• Neural Networks along with SMOTEENN resampling method consistently did well in predicting good movies after 100 training attempts (around 72% accuracy, 70% recall)
• Yes, it is possible to predict if a movie is good with acceptable amount of accuracy and recall

• Handling imbalanced datasets using resampling methods and imblearn package
• Neural Networks, Keras and Tensorflow
• Logistic Regression from sklearn
• API Usage
• Other packages such as tqdm, json, requests
• Collaborating using GitHub
• Concepts about Precision, Recall, and F1 Score

• https://developers.themoviedb.org/3/getting-started
• https://www.free-powerpoint-templates-design.com/old-style-movie-projector-powerpoint-templates/
• https://www.kaggle.com/rafjaa/resampling-strategies-for-imbalanced-datasets
• https://alexlenail.me/NN-SVG/index.html
• https://www.kdnuggets.com/2016/08/learning-from-imbalanced-classes.html/2
• https://arxiv.org/pdf/1608.06048.pdf
• https://machinelearningmastery.com/tutorial-first-neural-network-python-keras/
• https://towardsdatascience.com/derivative-of-the-sigmoid-function-536880cf918e
• https://www.researchgate.net/figure/Calculation-of-Precision-Recall-and-Accuracy-in-the-confusion-matrix_fig3_336402347
• https://medium.com/analytics-vidhya/confusion-matrix-accuracy-precision-recall-f1-score-ade299cf63cd