Страница телеграм канала Machine Learning World
Machine Learning World
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Все самое интересное в мире ИИ и Машинного обучения.
Входит в категории: Технологии
16.11.2019 12:11
How make smaller and faster network by knowledge got from big one?
https://blog.floydhub.com/knowledge-distillation/
15.11.2019 14:11
Create 3D scene from 1-2 images
https://arxiv.org/abs/1911.04554
13.11.2019 14:11
Interesting hardware news from Intel https://www.engadget.com/2019/11/12/intel-nervana-chips-for-ai-in-cloud/
11.11.2019 11:11
Hello, friends
After 2 months of sleepless nights and battles with gradients, were happy to share with you our new online course about Machine Learning - “Object Detection with PyTorch”
http://learnml.today
You may ask why we did it if there are so many similar courses? - And that’s a good question
The reason zero - we like ML and we like to teach people, cause thats one of the greatest things that u can give back to the community - knowledge that was gained by hard work and a huge amount of time spent. So the next generation can go farther from where we stopped.
The first reason - creating courses on some small area/problem/task to transfer knowledge to other specialists as fast as possible and without bullshit.
We are not professors from the university, we are practical guys who are paying their bills by doing researches and solutions in Machine Learning and AI areas. And as professionals, we often have a need to get new knowledge with deep understanding of problematic of tasks asap. But all we can find on the market is online courses about simple stuff that good for newcomers but not for us. And that’s a big problem because getting knowledge from papers is time-consuming.
The second reason - a huge gap between studying materials and real tasks. I think many of you had this feeling in the past when the teacher describe you something like 2+2 = 4, and then in real life, you get task to calculate the trajectory of a spaceship to Mars.
So we want to build courses from developers for developers, with giving real practical knowledge without gaps, so students can be ready for real-life after the course ends.
The course will lead you from the basics to the latest state-of-the-art solution and will consist of 7 lessons:
PyTorch Basics
Single Object Localisation
Single Shot Networks / Yolo
Single Shot Networks / SSD
Region Proposal Networks / Fast R-CNN
Region Proposal Networks / Mask R-CNN
Bonus Material
Requirements: Python, Base Math, ML Basics (CNN networks, Dense Networks)
Time: 4+ weeks (2 lessons/week but we will look by student progress)
Interaction with students: GitHub Issues
Environment(free): Google Colab, Ram: 12GB, Disk: 350GB, GPU: Nvidia T4 16GB
Start date: 18 November 2019
Also we have small demo tutorial for you: http://bit.ly/traffic-counting-with-opencv
You can subscribe on course on our page http://learnml.today
10.11.2019 12:11
Unsupervised Cross-lingual Representation Learning at Scale https://twitter.com/alex_conneau/status/1192490719031656448?s=19
08.11.2019 12:11
Guys, today we launched our Object Detection course on Product Hunt. And thats mean that as never before we need your support and upvoting power
Please go by link: https://www.producthunt.com/posts/object-detection-with-pytorch
Upvote our project and give a comment.
Many thanks)
08.11.2019 01:11
New cool post from Distill.Pub on computing receptive fields of CNN https://distill.pub/2019/computing-receptive-fields/
04.11.2019 13:11
Best paper on ICCV2019
SinGAN: Learning a Generative Model from a Single Natural Image https://arxiv.org/abs/1905.01164
30.10.2019 11:10
https://twitter.com/facebookai/status/1188953591026864128?s=19
28.10.2019 12:10
Open MMLab Detection Toolbox and Benchmark https://github.com/open-mmlab/mmdetection