Machine Learning Interview Prep!

Goal: To prepare those looking to transition into a MLE role.

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Currently this repo contains:

• Phone screen ML interview prep questions (algorithms, validation methods, stats)
• Practical coding sessions -- I recommend setting aside 90 minutes before starting any of these challenges in order to simulate the conditions a coding sessions during an ML onsite. View solutions only once you have completed your solution, and feel free to fork this repo to add your solutions!
• Code review checklist
• CS Practical Grading Rubric
• ML Jeopardy
• A Guide to GitHub & Collaborating
• Version Control with Git/Github
• Dockerized Data Science, a presentation from Manifold.AI on using Docker for ML models.

System Design

• ML System Design Flashcards, huge thanks goes out to Chip Huyen's ML repo for assisting!
• ML Terminology Falshcards, great to use for ML charades! Shoutout to Google Developers for assisting!
• System Design Outline
• System Design Workshop

Cloud Computing Resources: AWS

• AWS in plain English
• AWS Basics
• AWS Securitythings to know when getting started.
• Setting up your deep learning AMI
• Instructions for connecting Atom IDE to EC2
• Instructions for connecting to Jupyter on an EC2 instance
• Mounting S3 Bucket to EC2 Instance
• Boto + S3 bucket example
• Intro to SageMaker
• Sagemaker Overview
• Sagemaker Training Example
• Sagemaker Inference Example

Behavioral

• Questions to ask hiring managers before accepting an offer + negotiation tips

SWE for MLEs

• Data Structures and Algorithms
• Object Oriented Programming
• OOP w/ Python review
• Intro to Dynamic Programming

Intro to Data for MLEs

• Intro to Data Challenges
• Intro to Data Modeling
• Intro to Distributed Systems
• Intro to DevOps