After installing Tensorflow, for example with the last short Tutorial about Tensorflow setup on Windows, some may ask how to start with Tensorflow. Besides the official Tutorials on tensorflow site, which are going deep into the different parts and features of Tensorflow in a comprehensible form, i want to show you two more access points into the topic of deep learning and Tensorflow in particular.
First Contact – jupyter notebook files
In my opinion, the best way to learn about a new python Framework in a very playful manner are prepared jupyter (former iPython) notebook files. Fortunately google is delivering a small but high quality set of notebooks along with the tensorflow github package.
The first notebook hello_tensorflow.ipynb explains the basic principles of working with Tensorflow-tensors and -operators. getting_started.ipynb walks through an example of a very simple neural network for linear regression with gradient descent. The last notebook mnist_from_scratch.ipynb applies Tensorflow to the actual Hello World of Machine Learning, the MNIST handwritten digit dataset.