![Classical Machine Learning [DoorDash Data Science Project] @stratascratch](https://i.ytimg.com/vi/pqQG_tNXncc/maxresdefault.jpg)
Uploaded January 2023 | Updated September 2026, 7 hours ago
In this video, we'll be diving deep into machine learning for data science. We'll explore some of the most important concepts in machine learning and choose the best-performed model. We'll demonstrate how to apply these concepts in practice on the DoorDash data science project 'Delivery Duration Prediction'. We'll apply 6 different algorithms, 4 different feature set sizes, and 3 different scalers.
Watch our previous video:
📌 Part 1: Data Preparation for Modeling: youtu.be/Sf6jn8QZHhc
📌 Part 2: Collinearity and Removing Redundancies: youtu.be/m3zEV10qvE8
📌 Part 3: Multicollinearity and Feature Selection: youtu.be/gh5JzALBQvU
🧑💻 Go to the project through the link below and follow along with me: platform.stratascratch.com/data-projects/delivery-duration-prediction?utm_source=youtube&utm_medium=click&utm_campaign=YT+classical+ML+doordash+project
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👉 Subscribe to my channel: bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+classical+ML+doordash+project
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Timeline:
Intro: (0:00)
Take-home assignment from DoorDash: (0:23 )
In previous videos: (0:40)
Applying the data to the machine learning model: (1:14)
Applying regression tasks: (2:03)
Changing the problem: (5:17)
Extracting the Prep_duration predictions (7:20)
Deep Learning Method: (10:31)
Conclusion: (12:44)
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About The Platform:
I'm using StrataScratch (platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+classical+ML+doordash+project), 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?utm_source=youtube&utm_medium=click&utm_campaign=YT+classical+ML+doordash+project. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, 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
______________________________________________________________________
#StrataScratch #DoordashDataProject #MachineLearning
In this video, we'll be diving deep into machine learning for data science. We'll explore some of the most important concepts in machine learning and choose the best-performed model. We'll demonstrate how to apply these concepts in practice on the DoorDash data science project 'Delivery Duration Prediction'. We'll apply 6 different algorithms, 4 different feature set sizes, and 3 different scalers.
Watch our previous video:
📌 Part 1: Data Preparation for Modeling: youtu.be/Sf6jn8QZHhc
📌 Part 2: Collinearity and Removing Redundancies: youtu.be/m3zEV10qvE8
📌 Part 3: Multicollinearity and Feature Selection: youtu.be/gh5JzALBQvU
🧑💻 Go to the project through the link below and follow along with me: platform.stratascratch.com/data-projects/delivery-duration-prediction?utm_source=youtube&utm_medium=click&utm_campaign=YT+classical+ML+doordash+project
______________________________________________________________________
👉 Subscribe to my channel: bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: bit.ly/3jifw81
👉 Playlist for data science interview tips: bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+classical+ML+doordash+project
______________________________________________________________________
Timeline:
Intro: (0:00)
Take-home assignment from DoorDash: (0:23 )
In previous videos: (0:40)
Applying the data to the machine learning model: (1:14)
Applying regression tasks: (2:03)
Changing the problem: (5:17)
Extracting the Prep_duration predictions (7:20)
Deep Learning Method: (10:31)
Conclusion: (12:44)
______________________________________________________________________
About The Platform:
I'm using StrataScratch (platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+classical+ML+doordash+project), 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?utm_source=youtube&utm_medium=click&utm_campaign=YT+classical+ML+doordash+project. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, 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
______________________________________________________________________
#StrataScratch #DoordashDataProject #MachineLearning
![Classical Machine Learning [DoorDash Data Science Project]](https://i.ytimg.com/vi/pqQG_tNXncc/mqdefault.jpg "Classical Machine Learning [DoorDash Data Science Project]
In this video, well be diving deep into machine learning for data science. Well explore some of the most important concepts in machine learning and choose the best-performed model. Well demonstrate how to apply these concepts in practice on the DoorDash data science project Delivery Duration Prediction. Well apply 6 different algorithms, 4 different feature set sizes, and 3 different scalers.
Watch our previous video:
📌 Part 1: Data Preparation for Modeling: https://youtu.be/Sf6jn8QZHhc
📌 Part 2: Collinearity and Removing Redundancies: https://youtu.be/m3zEV10qvE8
📌 Part 3: Multicollinearity and Feature Selection: https://youtu.be/gh5JzALBQvU
🧑💻 Go to the project through the link below and follow along with me: https://platform.stratascratch.com/data-projects/delivery-duration-prediction?utm_source=youtube&utm_medium=click&utm_campaign=YT+classical+ML+doordash+project
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+classical+ML+doordash+project
Timeline:
Intro: (0:00)
Take-home assignment from DoorDash: (0:23 )
In previous videos: (0:40)
Applying the data to the machine learning model: (1:14)
Applying regression tasks: (2:03)
Changing the problem: (5:17)
Extracting the Prep_duration predictions (7:20)
Deep Learning Method: (10:31)
Conclusion: (12:44)
About The Platform:
Im using StrataScratch (https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+classical+ML+doordash+project), 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 https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+classical+ML+doordash+project. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, 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
#StrataScratch #DoordashDataProject #MachineLearning")
![[Part 1] How to Solve an Amazon Python Interview Question - The 3-Step Framework](https://i.ytimg.com/vi/rEaSskQhId4/mqdefault.jpg "[Part 1] How to Solve an Amazon Python Interview Question - The 3-Step Framework
In this video, well walk through Amazons advanced data science interview question and determine a 3-step framework to solve it in Python.
Part 2: https://www.youtube.com/shorts/vQmk0bH25d0
Link to the question: https://platform.stratascratch.com/coding/2111-sales-growth-per-territory?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
👉 Watch the full video: https://youtu.be/yQSZT65WET4
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link
About The Platform:
Im using StrataScratch (https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link), 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 https://platform.stratascratch.com/coding?utm_source=youtube&utm_medium=click&utm_campaign=YT+description+link. All questions are free and you can even execute SQL and python code in the IDE, but if you want to check out the solutions from me or from other users, 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
#PythonInterviewQuestions #AmazonPythonInterviewQuestion")
![Top Data Analyst Tools: From Beginner to Pro [Ultimate Guide]](https://i.ytimg.com/vi/sBD3HAbUDQU/mqdefault.jpg "Top Data Analyst Tools: From Beginner to Pro [Ultimate Guide]
Struggling to keep up with the ever-growing data analyst toolkit? This video dives into essential tools for data analysts, from project management to data cleaning, coding, visualization & more. Learn everything you need to excel in your data analytics career, whether youre a beginner or looking to upskill.
Well cover everything from:
◉ Project Management: Jira, Trello, Confluence
◉ Brainstorming & Mind Mapping: Miro, MindMeister
◉ Databases & SQL: SQL, MongoDB, Cassandra
◉ Data Gathering: APIs, BeautifulSoup, Scrapy, Octoparse
◉ Data Integration: Talend, Apache Nifi, Microsoft Power Automate
◉ Data Cleaning: OpenRefine
◉ Data Analysis & Visualization: Excel, Google Sheets, Python, R, Pandas, NumPy, ggplot2, Jupyter Notebooks
◉ Web Analytics: Google Analytics
◉ Statistical Analysis: SAS, SPSS
◉ ETL Tools: Apache Spark, Informatica, Alteryx
◉ Data Visualization: Tableau, Power BI, Looker Studio, ClickView
◉ Presentation Tools: PowerPoint, Google Slides, Canva
◉ Data Documentation: Jupyter Notebooks, R Markdown, Google Docs, Github
Master these tools and unlock a world of data-driven opportunities! Like this video? Thumbs up, share, and comment below! Subscribe for more data analytics content!
👉 Subscribe to my channel: https://bit.ly/2GsFxmA
👉 Playlist for more data science interview questions and answers: https://bit.ly/3jifw81
👉 Playlist for data science interview tips: https://bit.ly/2G5hNoJ
👉 Playlist for data science projects: https://bit.ly/StrataScratchProjectsYouTube
👉 Practice more real data science interview questions: https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+top+da+tools
Timeline:
Intro: (0:00)
What Do Data Analysts Do: (0:19)
Requirement-gathering Tools: (0:46)
Brainstorming Tools: (1:10)
Data Collection & Management: (1:30)
Data Cleaning & Analysis : (2:56)
Data Visualization Tools: (4:40)
Presentation Tools: (5:14)
Documentation Tools: (5:30)
Conclusion: (6:02)
About The StrataScratch Platform:
StrataScratch (https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+top+da+tools) is 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 https://platform.stratascratch.com/coding?code_type=1&utm_source=youtube&utm_medium=click&utm_campaign=YT+top+da+tools. 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 the StrataScratch team, 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 us at team@stratascratch.com
#dataanalysistools #datascience #machinelearning #bigdata #datavisualization #datascienceskills #datascientist #dataanalysis #dataanalytics #datatools")
