An early draft of the machine learning interviews book is out 🥳
The book is open-sourced and free. Job search is a stressful process, and I hope that this effort can help in some way.
Contributions and feedback are appreciated!
https://t.co/N1m3kNvZfo
One of the most well-known pieces of software for downloading YouTube videos, “youtube-dl” was removed from GitHub following a takedown notice from the Recording Industry Association of America, or RIAA.
Someone encoded the source code into two images and put it on Twitter:
We need your help...
We are seeking your input on what development areas AI4D innovations can and should prioritise in Africa. Your responses on this survey will inform the selection of development areas for our 4 Pan African innovation research networks https://t.co/qqLGScPDBh
We’re introducing M2M-100, the first multilingual machine translation model that translates between any pair of 100 languages without relying on English data. We’ve open sourced the model, training, & evaluation set up. Learn more https://t.co/9nszUF5nTj #t9n#machinetranslation
Some resources that I’ve found really helpful to understand machine learning in production.
1. Engineering starts with infrastructure. @vtuulos gave a great overview of the relationship between data science and infrastructure at Netflix
https://t.co/BrVrrG5HC0
From MIT nonetheless!
For free.
For those who are looking for a more structured approach to learn Computer Science and Python 🐍.
It even comes with Interactive Assessments!
https://t.co/HW4KEsnPY3
Just hit 500 stars on my Practical Deep Learning for Coders 2.0 (Walk with @fastdotai course) repo!!! Thank you so much guys, and I'm glad folks are finding it useful as time goes by😁https://t.co/z520flezjB
Sunday Video🤠 Choosing an Optimizer for Deep Learning is hard and often just done based on what other people do. Can we do better? This paper compares 14 of the most popular optimizers on 8 different DL problems in a 35K-run benchmark. 🤯
https://t.co/NDdRt97j0Y
@PhilippHennig5
Python is a beautiful programming language. It contains really useful features that make writing code more efficient than ever.
Here are 5 tips for writing more efficient and compact code.
🧵🧵🧵
Some areas of tech - like data science, machine learning, & computer graphics - require some math skills.
So you'll need to brush up on precalculus concepts to get into them.
Here's a free 5-hour course that'll teach you college math prerequisites.
https://t.co/8C186PcNHG
This Saturday 17th Oct - Sun 18th Oct, bring your best data science skills , reduce ambulance response time in Nairobi, and win prizes! Powered by @uber_kenya in partnership with @RescueByFlare @ZindiAfrica .. full details & rsvp on https://t.co/uv8pgutT1l
With overwhelming excitement that we can finally share with you "Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages" to be published at ✨Findings of @emnlp2020 ✨💕🌍💪🏾
Preprint: https://t.co/r01i7C9jFs
/1
Introducing TensorSensor: a lib that clarifies exceptions by augmenting messages + visualizing Python code to indicate shape of tensor variables; works with Tensorflow, PyTorch, Numpy, and higher-level libraries like Keras and fastai. Article: https://t.co/lqZgWOu4FC
The ultimate guide to encoder-decoder models!
Today, we're releasing part one explaining how they work and why they have become indispensable for NLG tasks such as summarization and translation.
> https://t.co/MbIRQMVtzU
Subscribe for the full series: https://t.co/O2BN6nth3I