Top all-time · #2798
svds.com
Company blog · svds.comdataprogrammingai
svds.com is the company blog at svds.com, writing about data, programming and ai. Since 2014, 27 different Hacker News readers have linked it 40 times, most often “Ethereum: The Rise of the World Computer”. No feed was found, so read it on the site itself.
Too few sampled comments (11) to say how often HN recommends it.?
Why HN links it
Linked as a source of practical machine learning and data engineering write-ups, such as TensorFlow on a Raspberry Pi, a deep learning getting-started guide, and Jupyter notebook reproducibility practices.
Summarised by Claude from a sample of 11 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.
Most-linked posts?
- Ethereum: The Rise of the World Computer3 people · 3 mentions · first linked 2016-02-23
- TensorFlow Image Recognition on a Raspberry Pi2 people · 2 mentions · first linked 2017-02-08
- Learning from Imbalanced Classes2 people · 2 mentions · first linked 2016-08-25
- TensorFlow RNN Tutorial2 people · 2 mentions · first linked 2017-03-23
What Hacker News says?
Ha! A friend sent me this comment when he recognized this project. Unless there happens to be another firm who did the exact same thing we did, I was a part of this project (see this blog post https://www.svds.com/introduction-to-trainspotting/ ). You misunderstood the point of the presentation. The company was a consulting firm that specialized in data science and engineering. Our clients wanted to kick the tires a…
Comment linking /introduction-to-trainspotting/
on “The First Rule of Machine Learning: Start Without Machine Learning”Submitted Ethereum: Rise of the World Computer as a story · 413 points
HN discussionNotebooks can be reproducible, they just aren’t automatically so. It requires a little bit of effort and discipline, if reproducibility is a goal. https://www.svds.com/jupyter-notebook-best-practices-for-dat... is an excellent starting point. Personally, I use notebooks to keep a record of large computational pipelines. The key is to cache all results to disk. This allows for an iterative process where I modify the…
Comment linking /jupyter-notebook-best-practices-for-data-science/
on “Jupyter Receives the ACM Software System Award”Submitted Getting Started with Deep Learning: A Review of Available Tools as a story · 268 points
HN discussionThere was a recent post on HN about getting a tensorflow model running on a raspberry pi to detect trains. The blog post describing the process was quite well done. I bet it would apply quite well to detecting deer. https://news.ycombinator.com/item?id=13603225 http://svds.com/tensorflow-image-recognition-raspberry-pi/
Comment linking /tensorflow-image-recognition-raspberry-pi/
on “Welcome to the New AWS AI Blog”Submitted TensorFlow Image Recognition on a Raspberry Pi as a story · 251 points
HN discussionMy colleagues and myself have a blog post discussing how to do streaming video analysis on the Raspberry Pi: https://svds.com/streaming-video-analysis-python/ On the Pi3, our application processes 320X240 images at 10 FPS without any problems. Let me know if you have any questions!
Comment linking /streaming-video-analysis-python/
on “TensorFlow Image Recognition on a Raspberry Pi”Submitted Avoiding a Common Mistake with Time Series as a story · 161 points
HN discussionHi Florin, thanks for the comment! Even with the heatsink (which we install on all of the Pis), we were still having overheating issues. We tried a few other things too to mitigate the problem: 1. Reducing sampling rate for the image recognition (but if we reduced this beneath several seconds we could miss the express trains) 2. Using a cooling fan ( https://www.amazon.com/gp/product/B013E1OW4G/ref=oh_aui_sear... )…
Comment linking /streaming-video-analysis-python/
on “TensorFlow Image Recognition on a Raspberry Pi”Submitted Learning from Imbalanced Classes as a story · 108 points
HN discussion>> Rebalancing an imbalanced dataset is common in industry and academicia. You use that when you focus on accuracy, to make claims like: We were 54% accurate on classifying sexuality of females easily interpretable, without needing a distribution-balanced benchmark (you simply know it is a coin flip). You quoted The Strength of Weak Learnability and I figured you must have at least a passing acquaintance with comput…
Comment linking /learning-imbalanced-classes/
on “We tested Europe’s new lie detector for travelers and triggered a false positive”Submitted Analyzing Caltrain Delays as a story · 64 points
HN discussionThis is very good - I've never seen a RNN-for-speech-in-Tensorflow model before. Note, though that the real problem here is the lack of training data. In a recent podcast I heard that the Baidu speech recognition team uses "small models" of 10,000 hours of speech. I forget how big the production quality models were, but it was at least 5 times that. This model uses ~1500 hours[1]. It's very impressive it does as wel…
Comment linking /tensorflow-rnn-tutorial/
on “Recurrent Neural Networks - A Short TensorFlow Tutorial”Submitted TensorFlow RNN Tutorial as a story · 36 points
HN discussionI found this to be informative - https://svds.com/getting-started-deep-learning/
Comment linking /getting-started-deep-learning/
on “Ask HN: Why TensorFlow instead of Theano for deep learning?”Submitted How I Learned to Stop Worrying and Love Ephemeral Storage as a story · 26 points
HN discussionWe've been working on the solution to this issue since our office is overlooking the tracks. You can read more here: http://svds.com/post/listening-caltrain and here: http://svds.com/post/railroad-modeling-hadoop-scale-hadoop-s...
Comment linking /post/railroad-modeling-hadoop-scale-hadoop-summit-2014-san-jose
on “I'd like Caltrain to publish raw train data”Submitted Open Source Toolkits for Speech Recognition as a story · 23 points
HN discussionThis is odd- the original article [0] was posted about a month ago, and this seems to be a repost with some ads thrown in. Hopefully mrubashkin submitted the article to Insight Data Science himself. [0]: https://svds.com/tensorflow-image-recognition-raspberry-pi/
Comment linking /tensorflow-image-recognition-raspberry-pi/
on “TensorFlow Image Recognition on a Raspberry Pi”Submitted Tuning Kafka and Spark Pipelines as a story · 21 points
HN discussionHere's an in depth answer: https://www.svds.com/getting-started-deep-learning/
Comment linking /getting-started-deep-learning/
on “Ask HN: Does it matter which deep learning framework I use?”Submitted How to Navigate the Jupyter Ecosystem as a story · 20 points
HN discussionSubmitted Machine Learning vs. Statistics: The Texas Death Match of Data Science as a story · 15 points
HN discussionSubmitted The Value of Exploratory Data Analysis (EDA) as a story · 15 points
HN discussionSubmitted Show HN: Brain Monitoring with Kafka, OpenTSDB, and Grafana as a story · 15 points
HN discussionSubmitted Ethereum: The Rise of the World Computer as a story · 15 points
HN discussionSubmitted Streaming Video Analysis in Python as a story · 9 points
HN discussionSubmitted How to choose between Avro and Parquet? as a story · 8 points
HN discussionSubmitted Mind Reading via TensorFlow Classification of EEG Brain Recordings as a story · 7 points
HN discussionSubmitted Listening to Caltrain: Analyzing Train Whistles with Data Science as a story · 7 points
HN discussion
