# Week 4 - Convolutional Neural Networks, Part I

### This week you will...

* go deeper into using ConvNets with real-world data and a much larger dataset than those you've been using thus far.
* learn about image augmentation, a technique to avoid overfitting by tweaking the training set to potentially increase the diversity of subjects it covers.
* discuss your project ideas.

### Slides

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### Learning Resources

* Week 1 and 2 of the course [Convolutional Neural Networks in TensorFlow](https://www.coursera.org/learn/convolutional-neural-networks-tensorflow)

### Until next week you should...

* complete week 3 and week 4 of the course [Convolutional Neural Networks in TensorFlow](https://www.coursera.org/learn/convolutional-neural-networks-tensorflow)
* complete the exercise assignment in [this notebook](https://colab.research.google.com/github/opencampus-sh/course-material/blob/main/machine-learning-with-tensorflow/week-04/241121_Assignment_CNN_Part-2.ipynb)
* investigate the characteristics of your project's dataset according to the instructions given [here](https://github.com/opencampus-sh/ml-project-template/blob/main/1_DatasetCharacteristics/INSTRUCTIONS.md)
* document your findings on the dataset characteristics according to the instructions of above
