# Week 8 - Neural Nets ### This week we will... * learn about different libraries for implementing neural nets * review example notebooks for the data preparation and training of neural net using Pandas and TensorFlow * get to know additional types of layers in neural nets ### Learning Resources {% file src="" %} * Additional [introduction video](https://www.youtube.com/watch?v=GvQwE2OhL8I) (12 Minuten) on neural nets * [Example data preparation notebook](https://colab.research.google.com/github/opencampus-sh/einfuehrung-in-data-science-und-ml/blob/main/Neuronale%20Netze/neural_net_data_preparation.ipynb) for a neural net * [Example notebook](https://colab.research.google.com/github/opencampus-sh/einfuehrung-in-data-science-und-ml/blob/main/Neuronale%20Netze/neural_net_estimation.ipynb) for training a neural net ### Until next week you should... * [x] watch [this video](https://www.youtube.com/watch?v=ARq74QuavAo\&list=PLkDaE6sCZn6Hn0vK8co82zjQtt3T2Nkqc\&index=7) (7 minutes) to better understand the properties of dropout layers. * [x] watch [this video](https://www.youtube.com/watch?v=FDCfw-YqWTE\&list=PLkDaE6sCZn6Hn0vK8co82zjQtt3T2Nkqc\&index=9) (5 minutes) to better understand the benefits of normalization. * [x] complete the first chapter of [this course](https://campus.datacamp.com/courses/dealing-with-missing-data-in-python/) on DataCamp to learn about identifying missing values.
* [x] examine all your model variables for the existence of missing and implausible values. * [x] prepare your dataset by correctly encoding all categorical features and removing all rows with missing values. * [x] train a first neural network for your dataset. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://opencampus.gitbook.io/opencampus-machine-learning-program/courses/einfuehrung/woche-7-neuronale-netze-und-deep-learning.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.