Closed alexeygrigorev closed 1 year ago
0:00:00 - Thanking viewers for contributions and updates. 0:01:49 - Tips for contributing to time codes. 0:03:47 - Overview of Week 2 content and homework 0:05:46 - How to structure technical interviews around projects 0:07:40 - Course overview and live coding demonstration. 0:09:35 - Emphasis on projects, not trivia questions. 0:11:24 - Late homework submission not accepted. 0:13:08 - Importance of Projects over Homeworks in Certification 0:15:14 - Intuition-based distribution shaping and homework evaluation. 0:17:27 - Using pandas for large data sets. 0:19:27 - Learn how to run machine learning in your database. 0:21:18 - Scikit-learn offers smarter ways for regression. 0:23:18 - Collect unique data for impactful project. 0:25:15 - Collecting data for portfolio projects is amazing. 0:27:06 - Career advice: Data engineer or scientist? 0:28:50 - Data science vs. data engineering & linear regression assumptions. 0:30:51 - Practical validation for linear regression models. 0:32:54 - Choosing an ideal tech stack for data science 0:34:56 - Deploying Docker containers with AWS Batch. 0:36:57 - Cross-validation best for improving model score. 0:39:07 - Data science course covers modeling and deployment.
Updated timecodes. Thank you!
Youtube video: https://www.youtube.com/watch?v=VojpszKmKw8