.@realSharonZhou is the instructor for our new GANs Specialization. Sharon is a CS PhD candidate at Stanford, advised by @AndrewYNg. Her work in AI spans from the theoretical to the applied — in medicine, climate, and social good. Read more on @coursera: https://t.co/KeNUBQ6zrC
Many devs are looking for data science jobs - so how can you stand out from the pack?
Well, you can update your portfolio, for starters.
In this article, @tyagi_harshit24 shows you how to build an awesome data science portfolio that'll get you noticed.
https://t.co/h3Mi1dA8vR
27 lessons in Machine Learning for Computer Vision. ~5 minutes each.
For free!
In a month from today, your future might look very different!
Here are the important details: 🧵👇
💫 Jupyter notebooks are out of this world!
In this blog, you’ll learn why Jupyter notebooks are an important part of our documentation infrastructure, how they help manage content, and improve collaboration.
Read how ↓ https://t.co/3P2gfbLrBi
Doing coding tutorials isn’t about memorizing syntax and algorithms... it’s about *learning what’s possible*.
If you know what’s possible, you can ask the right questions.
If you can ask the right questions, you can easily Google the answer.
No one memorizes everything.
I'm attending Data Science Festival - November 2020. A month of events - 20K Community Members - Unlimited free access
RT if you think others will find this helpful 🙌
https://t.co/b6alTAAuHl
Less than a week until you can get your hands on courses 1 + 2 of our new GANs Specialization!
Sign-up for GANs for Good - a virtual expert panel on September 30 with @AndrewYNg, @goodfellow_ian, @AnimaAnandkumar, Alexei Efros, & @realSharonZhou: https://t.co/FwzZVlAASA
We’re releasing KILT, a unified benchmark to help AI researchers evaluate #NLP models across multiple knowledge-intensive language tasks. https://t.co/5i5JND6IhM
The full hands-on tutorials, "Building Recommender Systems with PyTorch", are now available. We show how to build deep learning recommendation system and resolve the associated interpretability, integrity, and privacy challenges. See: https://t.co/vaqkdhpvyr
Here are 20 fundamental questions that you need to ace before getting a Machine Learning job.
Almost every company will ask these to weed out non-prepared candidates. You don't want to show up unless you are comfortable having a discussion about all of these.
🧵👇
Cool! Someone wrote a script that builds the face of an animal based on the population of the species. Each dot represents one animal, and as the populations increase or decrease the image will either become more discernible or disappear completely. #dataviz