interviews.ai
machine-learning-articles
| interviews.ai | machine-learning-articles | |
|---|---|---|
| 12 | 5 | |
| 4,437 | 3,108 | |
| - | - | |
| 0.0 | 4.1 | |
| over 2 years ago | about 2 months ago | |
| - | - |
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interviews.ai
- Deep Learning Interviews
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Ask HN: Leet code/CTCI equivalent for Data science/ML roles
scientists" - those interviews focus a lot of SQL, product metrics, A/B testing etc. You can also do SQL problems on leetcode for those types of positions.
2. Deep learning interviews book for ML positions - https://github.com/BoltzmannEntropy/interviews.ai - it's a bit too deep and advanced for most interviews though so don't be intimidated if you can't cover everything. Don't read this book if you're applying for a product DS position (and vice versa). You can also replace this with an ML theory book of your choice if you like.
3. Still leetcode and CTCI because they often come up for ML positions anyway.
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what to study for MLE interviews? Is it leetcode all the way?
Regarding how to study, my suggestion is to solve problems with sample datasets. A couple of books that might come in handy. 1. https://github.com/BoltzmannEntropy/interviews.ai - I like this because there are problems and solutions in there. 2. https://huyenchip.com/ml-interviews-book/
- Deep Learning Interviews book: Hundreds of fully solved job interview questions from a wide range of key topics in AI.
- GitHub - BoltzmannEntropy/interviews.ai: Deep Learning Interviews book: Hundreds of fully solved job interview questions from a wide range of key topics in AI
- Deep Learning Interviews: Hundreds of fully solved job interview questions from a wide range of key topics in AI
- Deep Learning Interviews book: Hundreds of fully solved job interview questions
machine-learning-articles
- CNN binary classification validation accuracy reached %77, yet performing poorly on test set?
- Guide to creating a VAE?
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Minimal PyTorch re-implementation of GPT
For anyone else who was new to the phrase "isotropic model":
https://github.com/christianversloot/machine-learning-articl...
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CNN Multiclass classification - What happens if in the last layer you use more units than classes?
Of course! I read the documentation and also usage examples and it seems like it should be used with softmax, receiving the class prediction
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How Vanishing/Exploding Gradient is solved by doing proper Weight Initialization?
Xavier initialization (tanh): https://cs230.stanford.edu/section/4/ He initialization (ReLU): https://github.com/christianversloot/machine-learning-articles/blob/main/he-xavier-initialization-activation-functions-choose-wisely.md
What are some alternatives?
machine-learning-roadmap - A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.
iris - Transformers are Sample-Efficient World Models. ICLR 2023, notable top 5%.
audio-ai-timeline - A timeline of the latest AI models for audio generation, starting in 2023!
minGPT - A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Awesome-pytorch-list - A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
embedding-encoder - Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.
high-school-guide-to-machine-learning - Being a high schooler myself and having studied Machine Learning and Artificial Intelligence for a year now, I believe that there fails to exist a learning path in this field for High School students. This is my attempt at creating one.
awesome-adaptive-computation - A curated reading list of research in Adaptive Computation, Dynamic Compute & Mixture of Experts (MoE).