Abstract: 

When I opened a neural network text book and saw the bunch of math formulas, I felt like "this is not for me". But wait, TensorFlow now provides the high-level API that let you write a few lines of Python code to get started with neural network, without understanding the hard math. Try this codelab to see how machine learning works on your laptop.

This codelab is designed as an easy TensorFlow introduction for non ML experts. All you need to know is how to use Python. It would take about 2 - 3 hours to go through all the sections.

Preparation: setting up the codelab environment with Cloud Datalab (Jupyter Notebook on GCP)
(https://goo.gl/WWnpqY)


Understanding neural network with TensorFlow Playgroud: See how "neuron" works with Playground demo
(https://goo.gl/2SJpFt)


Classify Manhattan with TensorFlow: Let's use TensorFlow to train the most basic neural network
(https://goo.gl/9H5Cxq)


Why deep neural network can get smarter?: Why neural network can get smarter? Build your own deep neural network with Playground and see how it works.
(https://goo.gl/yFuXix)

Classify MNIST images with TensorFlow: Use TensorFlow to train a neural network to clasisfy handwritten text images.
(https://goo.gl/SQSTqr)

Bio: 

Kaz Sato is Staff Developer Advocate at Google Cloud team, Google Inc. focusing on Machine Learning and Data Analytics products, such as TensorFlow, Cloud ML and BigQuery. Kaz has been speaking at major events including Google Cloud Next SF, Google I/O, Strata NYC etc., authoring many GCP blog posts, and leading developer communities for Google Cloud for over 8 years. He is also interested in hardwares and IoT, and has been hosting FPGA meetups since 2013.