Name: Machine Learning for Accounting with Python
Brand: University of Illinois Urbana-Champaign
Availability: OnlineOnly
Rating: 4.6 (8 reviews)

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学生对 University of Illinois Urbana-Champaign 提供的 Machine Learning for Accounting with Python 的评价和反馈

4.6

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43 个评分

课程概述

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. Accounting Data Analytics with Python is a prerequisite for this course. This course is running on the same platform (Jupyter Notebook) as that of the prerequisite course. While Accounting Data Analytics with Python covers data understanding and data preparation in the data analytics process, this course covers the next two steps in the process, modeling and model evaluation. Upon completion of the two courses, students should be able to complete an entire data analytics process with Python....

1 - Machine Learning for Accounting with Python 的 8 个评论（共 8 个）

创建者 Abdelkader G

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Feb 1, 2022

this great course , i'm accountant and i recomand for accountant to take all the course in order

创建者 Muhammad A K B M S

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Nov 6, 2022

The course overall is good but there is too much information for a beginner and plus there is no proper explanation in the videos like the second course of the specialization

创建者 Juan P G Z

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Dec 20, 2021

The information provided is very good, however it's very difficult to understand the teacher's accent.

创建者 Alex E

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Jun 10, 2021

This course is very well structured and formatted for better understanding the variety of methods in machine learning. I found the subjects quite challenging and without hints provided I am not sure if I was able to complete all the tasks. I want to say thanks to Linden Lu for his outstanding job.