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Machine Learning in Python: Main Developments and Technology Trends in Data Science, Machine Learning, and Artificial Intelligence

1
Department of Statistics, University of Wisconsin-Madison, Madison, WI 53575, USA
2
NVIDIA, Santa Clara, CA 95051, USA
3
Department of Comp Sci & Electrical Engineering, University of Maryland, Baltimore County, Baltimore, MD 21250, USA
*
Author to whom correspondence should be addressed.
Current address: 1300 University Ave, Medical Sciences Building, Madison, WI 53706, USA.
Information 2020, 11(4), 193; https://doi.org/10.3390/info11040193
Received: 6 February 2020 / Revised: 29 March 2020 / Accepted: 31 March 2020 / Published: 4 April 2020
(This article belongs to the Special Issue Machine Learning with Python)
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 machine learning and scalable general-purpose graphics processing unit (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. View Full-Text
Keywords: Python; machine learning; deep learning; GPU computing; data science; neural networks Python; machine learning; deep learning; GPU computing; data science; neural networks
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Raschka, S.; Patterson, J.; Nolet, C. Machine Learning in Python: Main Developments and Technology Trends in Data Science, Machine Learning, and Artificial Intelligence. Information 2020, 11, 193.

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