TensorFlow Introduction
We can think of ________ as variables, where we only define the type and dimension, but do not assign the value.
placeholders
TensorFlow's visualization toolkit
It provides the visualization and tooling needed for machine learning experimentation:
What is the main reasons of increasing popularity of Deep Learning? The advances in machine learning algorithms and research. The availability of massive amounts of data for training computer systems. The dramatic increases in computer processing capabilities. All of the above
All of the above are increasing the popularity of DL
Three parts of the TensorFlow architecture
The data is preprocessed, The model is built, The model is trained and estimated.
Why is TensorFlow the proper library for Deep Learning? It will benefit from TensorFlow's auto-differentiation and suite of first-rate optimizers It provides a collection of trainable mathematical functions that are useful for neural networks. It has extensive built-in support for deep learning All of the above
All of the above make TensorFlow the proper library for DL
What are the benefits of Keras's Functional API (select 3 answers)?
It can handle models with non-linear topology, It can handle models with shared layers, It can handle models with multiple inputs or outputs
Tensor structure
It helps us by giving us the freedom to shape the dataset in the way we want. It is particularly helpful when dealing with images, due to the nature of how information in images are encoded.
What is a Data Flow Graph?
A representation of data dependencies between operations
TensorFlow
It is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural
Which statement is TRUE about TensorFlow?
Runs on CPU and GPU
Which statement is FALSE about TensorFlow?
TensorFlow library is not proper for handling Machine Learning Problems
Keras is a high level API for building deep learning models. It provides limited control over the different nodes and layers in a network.
True - It is a high level API
In TensorFlow, tensors are multi-dimensional arrays with a uniform type (called a dtype). All tensors are immutable like Python numbers and strings: you can never update the contents of a tensor, only create a new one.
True - They are immutable and you can only create a new one
Fundamental elements of TensorFlow
Variables, Constants, Placeholders
Name two properties that a tensor has
a datatype and a shape
__________ cannot have their values changed.
constants
Session
it is used for executing the graph operations
________ are containers used to store values.
variables
