TensorFlow Tutorial 08 - Classify Lego Star Wars Minifigures | Full Project Walkthrough

New Tutorial series about TensorFlow 2! Learn all the basics you need to get started with this deep learning framework! Part 08: Classify Star Wars Lego Figures | Full Project Walkthrough In this part we use a real image dataset from Kaggle with Lego Star Wars Minifigures and do a full project walkthrough. I show you how to load the data using a tensorflow ImagaDataGenerator and implement a convolutional neural net to do image classification. I also introduce some new concepts like image augmentation and keras callbacks. ~~~~~~~~~~~~~~ GREAT PLUGINS FOR YOUR CODE EDITOR ~~~~~~~~~~~~~~ ✅ Write cleaner code with Sourcery: https://sourcery.ai/?utm_source=youtube&utm_campaign=pythonengineer * Get my Free NumPy Handbook: https://www.python-engineer.com/numpybook 🚀🚀 SUPPORT ME ON PATREON 🚀🚀 https://www.patreon.com/patrickloeber If you enjoyed this video, please subscribe to the channel! Course material is available on GitHub: https://github.com/patrickloeber/tensorflow-course Download the dataset: https://www.kaggle.com/ihelon/lego-minifigures-classification Links: https://www.tensorflow.org/api_docs/python/tf/keras/preprocessing/image/ImageDataGenerator https://www.tensorflow.org/tutorials/images/data_augmentation https://www.tensorflow.org/api_docs/python/tf/keras/callbacks/ You can find me here: Website: https://www.python-engineer.com Twitter: https://twitter.com/patloeber GitHub: https://github.com/patrickloeber Music: https://www.bensound.com/ #Python Course Parts: 01 TensorFlow Installation 02 TensorFlow Tensor Basics 03 TensorFlow Neural Net 04 TensorFlow Linear Regression 05 TensorFlow CNN (Convolutional Neural Nets) 06 TensorFlow Save & Load Models 07 TensorFlow Functional API 08 TensorFlow Multi-output Project 09 TensorFlow Transfer Learning 10 TensorFlow RNN / LSTM / GRU 11 TensorFlow NLP TensorFlow 2, Keras, Deep Learning, TensorFlow Course, TensorFlow Beginner Course, TensorFlow Tutorial ----------------------------------------------------