Uploaded May 2023 | Updated September 2026, 1 hour ago
Welcome back to our data project series from Rotten Tomatoes! In this video, we continue our journey to enhance our machine-learning models. We explore the power of feature selection and weighted random forest classifier to improve performance. Join us in the next video for more exciting insights. See you there!
Watch the previous parts:
π [Part 1]: Exploring and Visualizing Data For A Facebook Data Science Project of Movie Ratings: youtu.be/cM12QtrhdLo
π[Part 2]: Exploring Decision Tree Classifiers For A Facebook Data Science Project of Movie Ratings: youtu.be/Ih6G5hnn30Q
Go to the project through the link below and follow along with meπ
platform.stratascratch.com/data-projects/rotten-tomatoes-movies-rating-prediction?utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+3
______________________________________________________________________
π Subscribe to my channel: bit.ly/2GsFxmA
π Playlist for more data science interview questions and answers: bit.ly/3jifw81
π Playlist for data science interview tips: bit.ly/2G5hNoJ
π Playlist for data science projects: bit.ly/StrataScratchProjectsYouTube
π Practice more real data science interview questions: platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+3
______________________________________________________________________
Timeline:
Intro: (0:00βββ)
Splitting the Data: (0:58)
Feature Selection: (1:26)
Weighted Random Forest Classifier: (2:47)
Smote technique: (3:41)
Take away: (5:18ββ)
______________________________________________________________________
About The Platform:
I'm using StrataScratch (platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+3), a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and Python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+3. All questions are free and you can even execute SQL and Python code in the IDE. Still, if you want to check out the solutions from other users or from me, you can use ss15 for a 15% discount on the premium plans.
______________________________________________________________________
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
______________________________________________________________________
#datascienceproject
Welcome back to our data project series from Rotten Tomatoes! In this video, we continue our journey to enhance our machine-learning models. We explore the power of feature selection and weighted random forest classifier to improve performance. Join us in the next video for more exciting insights. See you there!
Watch the previous parts:
π [Part 1]: Exploring and Visualizing Data For A Facebook Data Science Project of Movie Ratings: youtu.be/cM12QtrhdLo
π[Part 2]: Exploring Decision Tree Classifiers For A Facebook Data Science Project of Movie Ratings: youtu.be/Ih6G5hnn30Q
Go to the project through the link below and follow along with meπ
platform.stratascratch.com/data-projects/rotten-tomatoes-movies-rating-prediction?utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+3
______________________________________________________________________
π Subscribe to my channel: bit.ly/2GsFxmA
π Playlist for more data science interview questions and answers: bit.ly/3jifw81
π Playlist for data science interview tips: bit.ly/2G5hNoJ
π Playlist for data science projects: bit.ly/StrataScratchProjectsYouTube
π Practice more real data science interview questions: platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+3
______________________________________________________________________
Timeline:
Intro: (0:00βββ)
Splitting the Data: (0:58)
Feature Selection: (1:26)
Weighted Random Forest Classifier: (2:47)
Smote technique: (3:41)
Take away: (5:18ββ)
______________________________________________________________________
About The Platform:
I'm using StrataScratch (platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+3), a platform that allows you to practice real data science interview questions. There are over 1000+ interview questions that cover coding (SQL and Python), statistics, probability, product sense, and business cases.
So, if you want more interview practice with real data science interview questions, visit platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+rotten+tomatoes+3. All questions are free and you can even execute SQL and Python code in the IDE. Still, if you want to check out the solutions from other users or from me, you can use ss15 for a 15% discount on the premium plans.
______________________________________________________________________
Contact:
If you have any questions, comments, or feedback, please leave them here!
Feel free to also email me at nathan@stratascratch.com
______________________________________________________________________
#datascienceproject










