Analyze Box Office Data with Seaborn and Python
Produce data visualizations with Seaborn
Apply graphical techniques used in exploratory data analysis (EDA)
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.
Навыки, которые вы получите
- Data Science
- Data Analysis
- Plotly
- Seaborn
- Data Visualization (DataViz)
Будете учиться пошагово
На видео, которое откроется рядом с рабочей областью, преподаватель объяснит эти шаги:
Data Loading and Exploration
Visualizing the Target Distribution
Comparing Film Revenue to Budget
Do Official Homepages Impact Revenue?
Distribution of Languages across Films
Common Words in Film Titles and Descriptions
How do Film Descriptions Impact Revenue?
Как устроены проекты с консультациями
Ваше рабочее пространство — это облачный рабочий стол в браузере. Ничего не нужно загружать.
На разделенном экране видео преподаватель предоставляет пошаговые
Рецензии
Лучшие отзывы о курсе ANALYZE BOX OFFICE DATA WITH SEABORN AND PYTHON
The course is good for complete beginners, but could have been better if we get the idea or design or the why of the project is structured the way it is. Thumbs up for the instructor and the course.
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 !
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.
Snehan is a great instructor. With this course you'll learn how to use some Seaborn plots and how to do some EDA with pandas.
Часто задаваемые вопросы
Часто задаваемые вопросы
Что я получу, приобретя проект с рекомендациями?
Доступны ли проекты с консультациями на ПК и мобильных устройствах?
Какие преподаватели ведут проекты с рекомендациями?
Можно ли скачать работу из уже завершенного проекта с рекомендациями?
Какие правила возврата средств?
Можно ли получить финансовую помощь?
Можно ли прослушать проект с рекомендациями и посмотреть видео бесплатно?
Какие предварительные знания требуются для работы над проектом с рекомендациями?
Можно ли выполнить этот проект с рекомендациями в веб-браузере, не устанавливая специальное ПО?
Как организована учеба на проектах с рекомендациями?
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