Machine Learning Notebooks

A curated set of applied machine learning notebooks with crawlable summaries, project context, and links to the full interactive notebook renderings.

  • Pizza Steak Image Classifier

    Binary image classification walkthrough using a Food-101 pizza and steak dataset, TensorFlow data loading, model training, and performance review.

  • Transfer Learning Fine-Tuning Experiments

    Experiment log for transfer learning models trained with different data volumes, augmentation, and fine-tuning setups.

  • Classification Intro

    Foundational classification notebook covering common classification types, neural network shapes, model runs, and evaluation.

  • Transfer Learning With TensorFlow

    Transfer learning walkthrough covering feature extraction, fine tuning concepts, Food-101 data prep, and TensorBoard logging.

  • Multi-Class Convolutional Neural Network

    Applied CNN notebook for ten-class image classification, including data inspection, model training, and overfitting checks.

  • Transfer Learning Fine Tuning

    Fine-tuning notebook that contrasts sequential and functional model-building approaches with TensorFlow image datasets.

  • Transfer Learning With 101 Food Classes

    Food-101 transfer learning notebook covering data preparation, dataset conversion, training, and loss-curve analysis.

  • Model Analysis In Depth

    Model analysis notebook focused on evaluating a 101-class classifier, inspecting predictions, and comparing predicted labels.

  • Modeling With Transformations

    Tabular modeling workflow showing data transforms, normalization, model training, and comparison with an earlier baseline.

  • Modeling And Wrangling

    Data wrangling and modeling notebook covering CSV loading, one-hot encoding, train/test splits, model fitting, and MAE review.