Tony Dunkin Hung (@Thung) profile picture

Machine Learning Engineer @progressive. Woodworker. I can go from Hardcore to Indie in 0.6 seconds. @tbass134@sigmoid.social

Rockin' the Suburbs
Joined November 2007
Photo by Tony Dunkin Hung (@Thung)Photo by Tony Dunkin Hung (@Thung)Photo by Tony Dunkin Hung (@Thung)Photo by Tony Dunkin Hung (@Thung)Photo by Tony Dunkin Hung (@Thung)Photo by Tony Dunkin Hung (@Thung)Photo by Tony Dunkin Hung (@Thung)Photo by Tony Dunkin Hung (@Thung)Photo by Tony Dunkin Hung (@Thung)Photo by Tony Dunkin Hung (@Thung)
Happy New Year Bitches!
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I’m working on a binary audio classification task using fbwav2vec via @huggingface. I only have about 1k samples, and I most likely need to use augment the dataset. What are people doing these days? Adding random noise? Volume changes?
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Finished up oiling two custom orders Ash / Purple Heart 42" charcuterie board Walnut 13" pizza peel And two flight boards in Sapele/ Ash / Purple Heart
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Soo creepy!! But really high quality hologram
Harry Caray hologram sings “Take Me Out to the Ballgame” #FieldofDreams 🎥: @MLBONFOX
I just answered today's machine learning question on @0xbnomial! I really love this! One ml question, everyday! You can give it a try here: today.bnomial.com
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Happy New Year Bitches!
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Kubernetes is pretty cool, but god damn, there’s a lot a crap to remember
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I’m doing 1 hour of personal dev time every day before work, but I’m not sure what to do, I was thinking about doing a kaggle comp, but is an hour a day enough? I’m also thinking of doing an ml course instead?
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I built my own mantel. Got some old beams from a lumber yard, made a box, stained and hung it up with a cleat I like how it came out instagram.com/p/CTZ4tCfstKR/…
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I was given a 13’ MBP for my new job, and it’s soo tiny. So I bought a USB-C portable monitor, and I love it. No external power, just one cable
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I have no idea how people get coding done on a 13’. It feels like using a netbook
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Super seriously..
This quoted post is unavailable.
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Coming from a non-academic background into ML, the way I started was just by building something . My very first ML project was a audio classifier to detect number of pills in a bottle. Not useful at all, but it showed team what is possible in ML. I just kept building from there
[1/n] I hosted a mentoring session at ICML and I got a lot of questions with a similar theme: "How do I get into ML?" I don't know. I generally try to not discuss what I don't know of, but since people seem to like to do that here, I thought I'd give it a try 🤣 Thread 👇🏻
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I'm working on a new set of blog posts that go over how to gather data, training and deploying models. The price of heating oil changes daily and I wanted a way to plot the prices and forecast the price in the future.
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So I built a way to pull oil prices from a website, save this data to an S3 bucket, and plot the prices using #streamlit. Also, I wanted to try out #pycaret, and I thought this is was a good way to get started.
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Welp, Im back on the market, looking for a ML role. I've been working in NLP as well as time series. RT are appreciated..
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new single from @deafheavenband is really different. like, i thought it was a different band different. Is the new record going to be similar to this?
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Never to early to learn about sorting!
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My PowerMac G5 coffee table!
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Bringing back my CoffeeBot App, now as an API. I've created a IOS Shortcut that gets your current location and returns the prediction ("Hot Coffee" or "Iced Coffee") icloud.com/shortcuts/df3f8e8…
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I originally made this into a IOS App a few years ago. The model behind it just predicts wether to drink hot or iced coffee, using the weather in your current location. I've trained the model with my own data for over 3 years, so its bias.
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keras is so much easier to work with than pytorch. Change my mind. please
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