trekhleb

11 ms·

91.
Show HN: Links Detector which makes printed links clickable(trekhleb.github.io)
3 points by trekhleb 6y ago|0 comments
92.
JavaScript Algorithms book is finally published(twitter.com)
1 points by trekhleb 6y ago|0 comments
93.
Generating cooking recipes using TensorFlow and LSTM RNN: A step-by-step guide(github.com)
9 points by trekhleb 6y ago|0 comments
94.
Don't let the social networks fool you into thinking that you can have it all(twitter.com)
3 points by trekhleb 6y ago|0 comments
95.
This is how social media could ruin your happiness(medium.com)
2 points by trekhleb 6y ago|0 comments
96.
Show HN: Weird recipes generator (RNN and TensorFlow)(trekhleb.github.io)
3 points by trekhleb 6y ago|0 comments
97.
by trekhleb 6y ago
I'm experimenting with Machine Learning (CNN, RNN, MLP) and TensorFlow in particular: https://github.com/trekhleb/machine-learning-experiments In the repository there are several experiments, each consists of Jupy
98.
Interactive Machine Learning Experiments with TensorFlow and Tensorflow.js(github.com)
3 points by trekhleb 6y ago|0 comments
99.
Show HN: Interactive Machine Learning Experiments(github.com)
4 points by trekhleb 6y ago|0 comments
100.
Show HN: Covid-19 dashboard with Сoronavirus distribution dynamics per country(trekhleb.github.io)
1 points by trekhleb 7y ago|1 comments
101.
Covid-19 dashboard to show the dynamics of Сoronovirus distribution per country(trekhleb.github.io)
3 points by trekhleb 7y ago|0 comments
102.
Ciara storm: this is how the 80km/h wind looks like(twitter.com)
6 points by trekhleb 7y ago|0 comments
103.
State-of-the-art Shitcode Principles your project should follow(github.com)
6 points by trekhleb 7y ago|0 comments
104.
by trekhleb 7y ago
The physics is really nice! Played with it for couple of minutes and even managed to drift/draw "2020" trace on the ground :D
105.
by trekhleb 7y ago
Thanks!
106.
by trekhleb 7y ago
Thanks! Glad that example was useful!
107.
by trekhleb 7y ago
It is possible. But don't have strict plans yet.
108.
by trekhleb 7y ago
Sure. Done.
109.
NanoNeuron – simple JavaScript functions that explain how machines learn(github.com)
377 points by trekhleb 7y ago|22 comments
110.
React hook usePosition() for fetching and following a browser geolocation(github.com)
2 points by trekhleb 7y ago|1 comments
111.
Creating React usePosition() hook for getting browser’s geolocation(itnext.io)
2 points by trekhleb 7y ago|0 comments
112.
Technical Interview Preparation Checklist(itnext.io)
5 points by trekhleb 7y ago|0 comments
113.
Technical Interview Preparation Checklist(medium.com)
6 points by trekhleb 7y ago|0 comments
114.
Interactive Jupyter/Python demos of popular machine-learning algorithms(github.com)
131 points by trekhleb 8y ago|2 comments
115.
Homemade machine learning on Python with interactive Jupyter demos(github.com)
64 points by trekhleb 8y ago|0 comments
116.
Jupyter/Python demo of digits recognition using logistic regression algorithm(nbviewer.jupyter.org)
4 points by trekhleb 8y ago|0 comments
117.
Interactive Jupyter/Python demo of Linear Regression right in your browser(nbviewer.jupyter.org)
8 points by trekhleb 8y ago|0 comments
118.
by trekhleb 8y ago
I've put my comments deeper in this thread. But just in case I'll also summarize them here. The links to the Andrew Ng course is on every README of the repo: on top of the main README.md and in the "References" section o
119.
by trekhleb 8y ago
Yes the code and comments were reformatted for better reading (in my opinion). Code has also been split differently than in the course: I was trying to distinguish some similarities between the algorithms like separate hypotheis() function,
120.
by trekhleb 8y ago
Yes, links to the Andrew Ng course is on every README of the repo: on top of the main README.md and in the "References" section of each internal README.md.

More ›