Machine Learning in Python: Main developments and technology trends in
data science, machine learning, and artificial intelligence
- URL: http://arxiv.org/abs/2002.04803v2
- Date: Tue, 31 Mar 2020 16:58:28 GMT
- Title: Machine Learning in Python: Main developments and technology trends in
data science, machine learning, and artificial intelligence
- Authors: Sebastian Raschka, Joshua Patterson, Corey Nolet
- Abstract summary: Python continues to be the most preferred language for scientific computing, data science, and machine learning.
This survey offers insight into the field of machine learning with Python, taking a tour through important topics to identify some of the core hardware and software paradigms that have enabled it.
- Score: 3.1314898234563295
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Smarter applications are making better use of the insights gleaned from data,
having an impact on every industry and research discipline. At the core of this
revolution lies the tools and the methods that are driving it, from processing
the massive piles of data generated each day to learning from and taking useful
action. Deep neural networks, along with advancements in classical ML and
scalable general-purpose GPU computing, have become critical components of
artificial intelligence, enabling many of these astounding breakthroughs and
lowering the barrier to adoption. Python continues to be the most preferred
language for scientific computing, data science, and machine learning, boosting
both performance and productivity by enabling the use of low-level libraries
and clean high-level APIs. This survey offers insight into the field of machine
learning with Python, taking a tour through important topics to identify some
of the core hardware and software paradigms that have enabled it. We cover
widely-used libraries and concepts, collected together for holistic comparison,
with the goal of educating the reader and driving the field of Python machine
learning forward.
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