# Week 5 - Convolutional Neural Networks, Part II

### This week you will...

* get familiar wit transfer learning, a powerful technique to include the knowledge of models that were trained on large datasets and benefit from the features these models already learned in your own problem scenario.
* move beyond binary classification into categorical classification and the specific coding considerations for the corresponding models.
* present your key findings for the literature review considering you selected project

### Learning Resources



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Presentation Slides from this week
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* Week 3 and 4 of the course [Convolutional Neural Networks in TensorFlow](https://www.coursera.org/learn/convolutional-neural-networks-tensorflow)

### Until next week you should...

* complete week 1 and week 2 of the course [Natural Language Processing in TensorFlow](https://www.coursera.org/learn/natural-language-processing-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-05/Week5_Notebook_Sentiment140.ipynb)
* decide on an evaluation metric for your project task and evaluate your baseline model
* justify why your choice is appropriate for your task
* document your decision in your GitHub repository
