Should we validate before we verify the software?
127 karma · joined October 3, 2018
I totally with this sentence. BUT If you ask for my opinion, merely knowing a list of statistical formulas is not very helpful. Most of the time, people don’t remember the underlying assumptions, so there is a fair chance they will use them in inappropriate situations.
I recommend watching these two YouTube videos. The presenters advocate using simulation/bootstrapping/shuffling methods instead of memorizing formulas.
Jake Vanderplas - Statistics for Hackers https://www.youtube.com/watch?v=Iq9DzN6mvYA
John Rauser - Statistics Without the Agonizing Pain https://www.youtube.com/watch?v=5Dnw46eC-0o
I believe you can achieve that if you use jupytext library, right?
If you are planning to build enterprise software solutions then I highly recommend this book. It contains very helpfull checklists and templates.
Not all posts are business related but you can learn many practical tricks hard to find in books.
> General-purpose language models can be fine-tuned to achieve several common tasks such as sentiment analysis and named entity recognition. These tasks generally don't require additional background knowledge.
> For more complex and knowledge-intensive tasks, it's possible to build a language model-based system that accesses external knowledge sources to complete tasks. This enables more factual consistency, improves reliability of the generated responses, and helps to mitigate the problem of "hallucination".
> Meta AI researchers introduced a method called Retrieval Augmented Generation (RAG) to address such knowledge-intensive tasks. RAG combines an information retrieval component with a text generator model. RAG can be fine-tuned and its internal knowledge can be modified in an efficient manner and without needing retraining of the entire model.
The easiness is relative (as you described) and depends on the things you are familiar with. For example, Docker containers and k8s stuff is easy (for you), and GraphQL is hard (for you).
The simplicity should be assessed (somehow) more objectively.
https://buttondown.email/hillelwayne/archive/edge-case-poiso...
Unfortunetely he passed away in 2019.
(user_courses
.set_index(["student_id",
"course_id"])
.unstack()
.apply(lambda x: x+1))I don't see why this is important.
> What you see is some of the daily data I’ve collected during the last 7 years of my life (2,498 days between 01/03/2014 and 01/01/2021) charted as basically as possible in order to allow global readings and comparisons. (A nice method is just to scroll up and down with the mouse cursor pointing to the time of interest.) I update it every January. I started to log some topics later on, and there is a period where I did not log mood for some technical reasons in mid-2015. I have a lot more data on medical issues, food, people, and daily activities, which I chose not to show here.
My tweets about this topic: https://twitter.com/arman_boyaci/status/1442436923960827913?...