Chevron Left
Analyze Box Office Data with Seaborn and Python に戻る

Coursera Project Network による Analyze Box Office Data with Seaborn and Python の受講者のレビューおよびフィードバック

4.5
174件の評価

コースについて

Welcome to this project-based course on Analyzing Box Office Data with Seaborn and Python. In this course, you will be working with the The Movie Database (TMDB) Box Office Prediction data set. The motion picture industry is raking in more revenue than ever with its expansive growth the world over. Can we build models to accurately predict movie revenue? Could the results from these models be used to further increase revenue? We try to answer these questions by way of exploratory data analysis (EDA) in this project and the next. The statistical data visualization libraries Seaborn and Plotly will be our workhorses to generate interactive, publication-quality graphs. By the end of this course, you will be able to produce data visualizations in Python with Seaborn, and apply graphical techniques used in exploratory data analysis (EDA). This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

人気のレビュー

AD

2020年6月5日

Everything taught was understood. Well explained. Looking for more projects from the instructor! Thank you! It was a great experience and I learnt a lot !

MA

2020年12月22日

Mr. Kekre was elaborative, clear, neat, and direct in illustrating the project, this is not overpraising; I would like to attend more projects for him.

フィルター:

Analyze Box Office Data with Seaborn and Python: 1 - 25 / 27 レビュー

by Mario C M

2020年6月9日

by Ritesh S

2020年5月26日

by Kalaiarasi N

2020年6月3日

by Aparajita D

2020年6月6日

by M B A

2020年12月23日

by Raghav G

2020年7月30日

by Nihar S

2020年5月11日

by Deleted A

2020年5月13日

by daniel s

2020年5月30日

by Veeramanickam M

2020年4月23日

by Joey L

2020年5月21日

by HAY a

2020年8月20日

by Archit M

2020年6月22日

by Ma. A S

2020年10月3日

by Gregory G J

2021年1月9日

by cristhian e c t

2021年1月4日

by tale p

2020年6月17日

by Anantharaman K

2020年7月12日

by Ananna B

2020年5月21日

by Rohan L

2020年5月4日

by Bahar R

2020年5月28日

by Manzil-e A K

2020年7月26日

by Muhammad A B

2020年8月12日

by Jorge G

2021年2月25日

by Amal N L

2020年7月23日