This course, Machine Learning for Accounting with Python, introduces machine learning algorithms (models) and their applications in accounting problems. It covers classification, regression, clustering, text analysis, time series analysis. It also discusses model evaluation and model optimization. This course provides an entry point for students to be able to apply proper machine learning models on business related datasets with Python to solve various problems.
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Habilidades que obtendrás
Universidad de Illinois en Urbana-Champaign
The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.
- 5 stars73,52 %
- 4 stars20,58 %
- 3 stars2,94 %
- 1 star2,94 %
Principales reseñas sobre MACHINE LEARNING FOR ACCOUNTING WITH PYTHON
The course is a great one for Machine Learning Journey
This is a great introductory course on machine learning with really practical examples. It does not go too deep.
Acerca de Programa especializado: Accounting Data Analytics
This specialization develops learners’ analytics mindset and knowledge of data analytics tools and techniques. Specifically, this specialization develops learners' analytics skills by first introducing an analytic mindset, data preparation, visualization, and analysis using Excel. Next, this specialization develops learners' skills of using Python for data preparation, data visualization, data analysis, and data interpretation and the ability to apply these skills to issues relevant to accounting. This specialization also develops learners’ skills in machine learning algorithms (using Python), including classification, regression, clustering, text analysis, time series analysis, and model optimization, as well as their ability to apply these machine learning skills to real-world problems.
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