Preprocessing - Keras
Here I go over Preprocessing, which is super important when you're working with data and want to do some transformations to it beforehand in order to use it to do machine learning.
I first start of with a brief explanation of simple preprocessing such as making an array of categories categorical, etc. The other type of super basic preprocessing that I go over is the normalization of data (which is something you always want to do).
We then go over sequence preprocessing and where I explain multiple preprocessing concepts and tools such as: “padding” of a sequence of actions; using skipgrams (incredibly useful if you’re doing any "one-hot vector" type stuff); natural language text preprocessing (including an overview of using the classic tokenizer).
Then, we move onto image preprocessing. Here I show you some cool ways to augment your image/data with random shifts and permutations like: image rotation, shifting width and length, sheering images, zooming, horizontal/vertical shift, rescaling, etc) after which I show you all of these image preprocessing techniques in action!
Links:
1) Link to my SciKit Learn Preprocessing video: • Preprocessing in Scikit Learn
2) Link to my SciKit Learn Datasets video: • Datasets in Scikit Learn
3) Link to my Scikit Learn tutorial - A Bit of DataScience and Scikit Learn: • Intro to Scikit Learn
4) The Hitchhiker's Guide to Python - one of the best handbooks to the installation, configuration, and usage of Python that I have come across: http://docs.python-guide.org/en/latest/
5) Link to Keras: https://keras.io
6) Link to TensorFlow: https://www.tensorflow.org
7) GitHub link to a-bit-of-deep-learning-and-keras notebooks: https://github.com/knathanieltucker/a...
8) Link to the History of Deep Learning video will be up soon!
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