1.5 AI Development Frameworks

Question 1

compilation of models to run on various processors, such as

Answer 1

central processing units (CPUs),
graphical processing units (GPUs)
or
Cloud Tensor Processing Units (TPUs).

Question 2

AI development frameworks

Answer 2

support a range of activities, such as
data preparation,
algorithm selection,
and compilation of models to run on various processors

Question 3

The selection of a particular framework

Answer 3

may also depend on particular aspects such as the programming language used for the implementation and its ease of use.

Question 4

Apache MxNet

Answer 4

is a deep learning open-source framework used by Amazon for Amazon Web Services (AWS) [R02].

Question 5

CNTK

Answer 5

is the Microsoft Cognitive Toolkit (CNTK), an open-source deep-learning toolkit [R03].

Question 6

IBM Watson Studio

Answer 6

is a suite of tools that support the development of AI solutions [R04].

Question 7

Keras

Answer 7

is a high-level open-source API, written in the Python language, capable of running on top of TensorFlow and CNTK [R06].

Question 8

PyTorch

Answer 8

is an open-source ML library operated by Facebook and used for apps applying image processing and natural language processing (NLP). Support is provided for both Python and C++ interfaces [R07].

Question 9

Scikit-learn

Answer 9

is an open-source machine ML library for the Python programming language [R08].

Question 10

TensorFlow

Answer 10

is an open-source ML framework based on data flow graphs for scalable machine learning, provided by Google [R05].

Question 11

AI development frameworks are constantly

Answer 11

evolving, sometimes combining, and sometimes being replaced by new frameworks.