How to use Tensorflow Keras API
You can use these APIs all together. E.g. if you have a regular dense network, but with an special layer you can use higher level API for dense layers (tf.layers and tf.keras) and low level API for your special layer.  Furthermore, it is complex graphs are easier to define in low level APIs, e.g. if you want to share variables, etc. 
Eager execution helps you for fast debugging, it evaluates tensors directly without a need of invoking a session.
Well I start learning Tensorflow but I notice there's so much confusion about how to use this thing..
First, some tutorials present models using low level API tf.varibles, scopes...etc, but other tutorials use Keras instead and for example to use tensor board to invoke callbacks.
Second, what's the purpose of having ton of duplicate API, really what's the purpose behind  using high level API like Keras when you have low  level to build  model like Lego blocks?
Finally, what's the true purpose of using eager execution?