Whether part of your job, school, or just spare time — have you made use of this branch of our field?
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Top comments (33)
Yes! made a tool to distinguish between ripe and unripe fruits.Unfortunately it's lost in the voids
That's a pretty neat application. I'm sure this sort of thing is already becoming part of the grocery supply chain.
yea nowadays, but back in the days this was pretty cool ngl
woah thats really cool! how did u do it?
Yes! To make a recommendation system for Stack Overflow unanswered questions
Recommendation system for Stack Overflow unanswered questions
It even allows you to make your own recommendation model, so people who also have experience with ML/NLP can tune even finer if they want ;)
I've been wanting to & over the weekend applied a deep learning model for facial recognition! Was pretty fun 😄
Facial recognition + good faces bot = best faces 🏆
Bryce Dorn ・ May 30 ・ 3 min read
I just finished my project on grain analysis (rice and lentil) to produce quality biodiesel. Used OpenCV so I could classify grains based on lenght-breadth ratio and color. First time doing a research like this but I had a lot of fun.
Wow! Fascinating. What is next for you?
Interviewer: What is your biggest strength?
Me: I am an expert in machine learning.
Interviewer: What’s 6 + 10?
Me: Zero.
Interviewer: Nowhere near. It’s 16.
Me: Ok, It’s 16.
Interviewer: What is 10 + 20?
Me: It’s 16.
Most interesting thing I did was trying to make a music genre identifier using Tensorflow.
I got some results but got kinda bored, never been a big fan of ML. Don't like collecting and labeling data. I could've probably used some api or something to label the music, but couldn't be botherer if I'm honest.
thats really cool! how did u make it?
I've made AI Profile Picture Maker for AI people:
mburakerman.github.io/ai-profile-p...
I have a cross-language (trans) compiler I wrote years ago and I've working on adding AI/ML features to improve it. The most interesting adjustment I have made was to incorporate feature vectorizations on the parsing side and use that in code generation and optimization. I'm still discovering and researching how best to use AI/ML in these tools, and I don't work on it too often since it is a side project. But after only a few months I can already see advantages.
Think about it like this... feature vectorization of the syntax creates binary patterns that can be handled as image recognition problems. So you take the code and convert it to binary, as all compilers do, but instead of converting it to machine code, you vectorize it as features. Those features have patterns that can tell you how to handle code generation and that image recognition can address for optimization.
And yes, I am aware that compilers are not a good fit for traditional AI/ML per say. But we can use AI/ML in various parts of the process to make it work better and require less development efforts.
I would like to think so. Not to promote too much, but the company I'm a part of (plainsight.ai) is creating a nice platform for anyone to do Computer Vision ML/AI. I've used it a few times to help me more accurately predict when my friends and myself should duck and cover from severe weather :D.
I've been tinkering with a chatbot to help me discover / cook recipes. Right now I'm using mostly pre-trained NLP models for the document embeddings and semantic search, which work decent enough for now. I'm planning to fine tune the NLP models to improve search results and maybe add a voice integration with some QA models so I can ask "how much salt do I need?" and get a response instead of always looking back at the recipe.
An early prototype is available here. I mostly work with data on a day-to-day basis so this has also been a learning experience with front-end dev and application deployment!