jalammar

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31.
A Visual Intro to NumPy and Data Representation(jalammar.github.io)
366 points by jalammar 7y ago|21 comments
32.
Intro to word2vec recommenders and how Airbnb and Alibaba use them [video](infoq.com)
1 points by jalammar 7y ago|0 comments
33.
by jalammar 8y ago
Thanks! Mostly Keynote, and lots of iteration. I'll be honest, I personally found this figure puzzling. Still not 100% clear on it, but I don't believe it refers to the negative sampling approach. My best guess is that it's r
34.
by jalammar 8y ago
You're the first to point that one out! Nice catch!
35.
by jalammar 8y ago
Oh wow. Hi Radim! Huge fan of Gensim! Thanks for the links!
36.
by jalammar 8y ago
Very interesting. I'll read the paper to wrap my head around the concept. Thanks for the feedback!
37.
by jalammar 8y ago
Hello HN, Author here. I wrote this blog post attempting to visually explain the mechanics of word2vec's skipgram with negative sampling algorithm (SGNS). It's motivated by: 1- The need to develop more visual language around embed
38.
The Illustrated Word2vec(jalammar.github.io)
348 points by jalammar 8y ago|37 comments
39.
by jalammar 8y ago
Hello HN, author here. This post is my best attempt at visually explaining some of the leading NLP models that came up this year and some of the context surrounding them. Given BERT relies on the Transformer model, this post builds on my ea
40.
The Illustrated BERT, ELMo, and Co. (How NLP Cracked Transfer Learning)(jalammar.github.io)
4 points by jalammar 8y ago|1 comments
41.
by jalammar 8y ago
Thanks for the heads up! Indeed it's df.loc[1:3] that would return three rows, not straight-up df[1:3] which indeed returns two rows. Edit: Corrected in the post. Thanks again!
42.
by jalammar 8y ago
I haven't used tidyverse myself, but I know that pandas is heavily influenced and inspired by R. Most analysis tasks are doable in both platforms. If later stages of your pipeline involve deep learning (or machine learning, generally),
43.
by jalammar 8y ago
A reasonable next step would be pick up a dataset that interests you (in a domain you're comfortable with) and explore it with pandas. Kaggle has a bunch of data sets ( https://www.kaggle.com/datasets ) in various domain
44.
by jalammar 8y ago
Hello HN, author here. If you've ever wanted to get into data analysis, this is my best attempt at getting you past that first hump. A lot of these concepts are easier than you might think.
45.
A Gentle Visual Intro to Data Analysis in Python Using Pandas(jalammar.github.io)
195 points by jalammar 8y ago|51 comments
46.
The Illustrated Transformer – A Visual Explanation for Attention Is All You Need(jalammar.github.io)
3 points by jalammar 8y ago|1 comments
47.
by jalammar 8y ago
Hello HN, Author here. I'd advise viewing on desktop since the post is loaded with animations and some details might be too small to view on mobile. I'd appreciate any feedback. Hope you find it useful.
48.
Visualizing a Neural Machine Translation Model (Mechanics of Seq2seq+Attention)(jalammar.github.io)
2 points by jalammar 8y ago|1 comments
49.
Visualizing Pandas' Pivoting and Reshaping Functions(jalammar.github.io)
1 points by jalammar 8y ago|0 comments
50.
by jalammar 9y ago
Hello HN, author here. As the title says, this post visualizes three of the most basics math operations involved in neural nets: 1- Calculating a prediction in a trained network 2- Sigmoid 3- ReLU It's meant mainly to encourage people
51.
A Visual and Interactive Look at Basic Neural Network Math(jalammar.github.io)
4 points by jalammar 9y ago|3 comments
52.
by jalammar 10y ago
https://d3js.org/
53.
by jalammar 10y ago
Glad you found it useful! Thanks for your feedback!
54.
by jalammar 10y ago
Even though it's posted on my blog, I hope this fits the bill for "Show HN" since the interactive parts can be tinkered and played with. I'd love any feedback or corrections.
55.
Show HN: A Visual and Interactive Guide to the Basics of Neural Networks(jalammar.github.io)
63 points by jalammar 10y ago|8 comments
56.
by jalammar 11y ago
What about a horizontal bar chart (ordered by value)? Yes you'll have to scan the list to find Wyoming, but it would better relate how Wyoming compares to West Virginia (which seems to have almost the same size square in the cartogram)
57.
by jalammar 11y ago
Thanks, man! Glad to see you enjoyed it! I'm going through the course as well! The Python route is certainly the easiest to get your hands dirty with TensorFlow, I must say.
58.
by jalammar 11y ago
Hi HN. OP here. Long time lurker. My first tech blog post. I basically tried here to clarify the Android app example that was bundled with the TensorFlow repo. Hope someone finds it useful.
59.
Supercharging Android Apps with TensorFlow (Google's Open Source ML Library)(jalammar.github.io)
6 points by jalammar 11y ago|3 comments
60.
by jalammar 11y ago
D3 Stickers link: https://www.stickermule.com/user/1070696243/stickers Mike, your work never fails to inspire. The cubism slides ( http://bost.ocks.org/mike/cubism/intro/#0 ) read lik

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