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This repo contains my solutions to “Introduction to Machine Learning Interviews” by Chip Huyen.
Machine Learning Engineering Open Book
A collection of full time roles in SWE, Quant, and PM for new grads.
Curriculum and roadmap from 0 to Mastery for MLOps. Adding value to your machine learning model by deploying it for people to use it to solve real life problems
📺 Discover the latest machine learning / AI courses on YouTube.
A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.
Causal Inference and Discovery in Python by Packt Publishing
Curated list of data science interview questions and answers
Answers to 120 commonly asked data science interview questions.
Interview Questions and Answers for Machine Learning Engineer role
Approaching (Almost) Any Machine Learning Problem
Quantitative Interview Preparation Guide, updated version here ==>
Supplementary Materials for the Deep Learning Book by Ian Goodfellow et al
An assignment for CMU CS11-711 Advanced NLP, building NLP systems from scratch
Collection of scripts and tools related to machine learning
Summaries and resources for Designing Machine Learning Systems book (Chip Huyen, O'Reilly 2022)
The guide to online assessments and interviews
Self-study on Larry Wasserman's "All of Statistics"
☁️ Azure summary in bullet points
💡algorithmsilluminated.org by Tim Roughgarden
Common GOF Patterns implemented in Python
Code repository for O'Reilly book
Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
All Algorithms implemented in Python