e_ameisen

7 ms·

1.
When Models Manipulate Manifolds: The Geometry of a Counting Task(transformer-circuits.pub)
5 points by e_ameisen 1y ago|0 comments
2.
by e_ameisen 1y ago
Hi, paper author here. This is a new tool which relies on existing introspection libraries like TransformerLens (which is similar in spirit to Garcon) to build an attribution graph. This graph displays intermediate computational steps the m
3.
Claude 3 can generate blog posts from videos(twitter.com)
7 points by e_ameisen 3y ago|1 comments
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ML models don't need that much data to be better than you(mlpowered.substack.com)
2 points by e_ameisen 4y ago|1 comments
5.
Local working implementations of distributed ML model training(github.com)
3 points by e_ameisen 4y ago|0 comments
6.
by e_ameisen 6y ago
http://mlpowered.com/ I share practical tips about ML. I focus specifically on things that will make it easier to ship ML applications. As much as possible, I include code. Popular posts: https://mlpowered.com&#x
7.
by e_ameisen 7y ago
Disclaimer: This is a book I wrote. Building Machine Learning Powered Applications walks you through building an ML application end-to-end, from product idea to a (simple) deployed version. The free first chapter is available here https:&#
8.
by e_ameisen 7y ago
I'm glad you have found a workaround. Again, this is for an example script outside of the main narrative of the book, so the impact should be minimal. If pip struggles to find a specific version, I'll usually remove the specific v
9.
by e_ameisen 7y ago
Interesting. I wasn't aware of that issue. It seems like after running activate, `pip` does point to the right location (`which pip` points to the virtualenv pip), but I'll look into it.
10.
by e_ameisen 7y ago
Sorry to hear that! Has tensorflow been your main issue? It is only used in one of the example notebooks, so you can skip that requirement without too much of an impact. If I can help with troubleshooting, send me an email at mlpoweredappli
11.
by e_ameisen 7y ago
That’s a great question, and I’m not sure. Googling around led me to an HN thread where a commenter claims that it is TheSans (lucasfonts.com/fonts/the-sans) but I do not have a good enough eye to confirm!
12.
by e_ameisen 7y ago
O'Reilly did organize the tech review process, where they found multiple reviewers to give detailed feedback on every part of the book. The O'Reilly staff themselves helped immensely with the editing process, as well as decisions
13.
by e_ameisen 7y ago
I answered the next comment down the chain, but I agree with you. As framed, there is no satisfactory solution to making a question "good". Improving question quality could however be a product goal for StackOverflow, or for a com
14.
by e_ameisen 7y ago
I'm so glad to hear you have been enjoying it!
15.
by e_ameisen 7y ago
I do not have a slack room, but that does sound like a good idea. For now I do have an email address provided for any questions in the book, and am reachable on Twitter (mlpowered) and GitHub.
16.
by e_ameisen 7y ago
Yes, this is the approach in the book. The concept of question quality is nuanced, and does not have a clear definition. It can be easy to feel like you've solved the problem by just throwing in ML and calling it a day, but producing s
17.
by e_ameisen 7y ago
Not at all, choose whichever platform and medium will give you the best reading experience. I hope you find the book helpful, please reach out if you have any questions or feedback.
18.
by e_ameisen 7y ago
It should be! The book mostly focuses on how to apply ML in practical concepts, and less about the internal workings of ML methods. I tried to explain the vast majority of ML concepts that I mention in the book. If you'd like to dive d
19.
by e_ameisen 7y ago
I recently published my first book! Writing a book has been a personal goal for the longest time, and Hacker News is the main reason I got to do so. Reading interesting posts on HN daily eventually inspired me to write my own, and posting m
20.
Show HN: My ML applications book, which HN helped me write (sample chapter) [pdf](mlpowered.com)
272 points by e_ameisen 7y ago|37 comments
21.
Thank/Show HN: You Helped Me Write an O'Reilly Book
2 points by e_ameisen 7y ago|0 comments
22.
by e_ameisen 7y ago
A lot of the resources proposed in the comments focus on theoretical knowledge, or a particular sub-domain (Reinforcement Learning, or Deep Learning). I recommend a top down approach where you pick a project and learn by building it. This c
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End-to-End Object Detection for Furniture Using Deep Learning(blog.insightdatascience.com)
1 points by e_ameisen 7y ago|0 comments
24.
Using Transfer Learning for NLP with Small Data(blog.insightdatascience.com)
2 points by e_ameisen 7y ago|0 comments
25.
by e_ameisen 7y ago
Great article! Add to it the moral cost of interviewing multiple subpar candidates and improving the fit of candidates at the top of the interview process has a huge impact. This is one of the reasons that many companies work with us at Ins
26.
AutoML for Data Augmentation(blog.insightdatascience.com)
3 points by e_ameisen 8y ago|0 comments
27.
Tackling Bias in Machine Learning(blog.insightdatascience.com)
1 points by e_ameisen 8y ago|0 comments
28.
Better Preference Predictions: Tunable and Explainable Recommender Systems(blog.insightdatascience.com)
2 points by e_ameisen 8y ago|0 comments
29.
Why NYC Is a Great Place to Break into AI(blog.insightdatascience.com)
2 points by e_ameisen 8y ago|0 comments
30.
State-of-the-art pre-training for natural language processing with BERT(blog.insightdatascience.com)
2 points by e_ameisen 8y ago|0 comments

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