Machine Learning Interview Prep
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37 learners
What you'll learn
This course includes
- 9.5 hours of video
- Certificate of completion
- Access on mobile and TV
Course content
1 modules • 24 lessons • 9.5 hours of video
Machine Learning Interview Prep
24 lessons
• 9.5 hours
Machine Learning Interview Prep
24 lessons
• 9.5 hours
- ML Coding Interviews Explained 03:31
- Machine Learning Conceptual Interviews (In 4 Minutes) 03:39
- Deploying a Machine Learning Model (in 3 Minutes) 03:36
- ML Engineer Interviews Explained (in 5 Minutes) 04:59
- Machine Learning Interview - Implement a 2D Convolutional Filter (with Senior Meta ML Engineer) 43:05
- ML Coding Question - Implement K-Means (Full Mock Interview with Snapchat MLE) 33:55
- ML System Design Mock Interview - Build an ML System That Classifies Which Tweets Are Toxic 51:47
- ML Coding Question - KNN Algorithm (Full mock interview with Snapchat MLE) 33:05
- ML Design and Coding Question - Design an ML Model To Predict App Deletion (Full mock interview) 01:33:15
- Instagram ML Question - Design a Ranking Model (Full Mock Interview with Senior Meta ML Engineer) 48:20
- Top 6 ML Engineer Interview Questions (with Snapchat MLE) 20:05
- Handling Exploding Gradients in Machine Learning 02:31
- When to Refresh an ML Model 03:14
- Classification vs. Regression in Machine Learning 02:38
- Importance of Feature Scaling and Normalization 01:08
- Gradient Descent Explained: Batch, Mini-Batch, and Stochastic (Simple) 05:19
- ML Training Data vs. Testing Data (Key Differences) 02:04
- ML System Design Question - Create an ETA System for Maps (Full mock interview) 56:20
- Netflix ML Question - Design a System to Predict Netflix Watch Times (Full mock interview) 28:03
- Spotify ML Question - Design a Recommendation System (Full mock interview) 33:47
- Machine Learning Question - Training AI to Detect Bots (Full mock interview) 37:38
- Fake News Detection System - Machine Learning Mock Interview 16:08
- How to Become a Machine Learning Engineer 09:37
- Amazon Machine Learning Engineer Interview: K-Means Clustering 32:33
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