last day of work for a week. (I'll work the 30th, so not QUITE for the year)
and my amazing "gift" from a colleague is 1500+ lines of example python for model building and preprocessing and validation! He writes beautiful, readable code too!
I am _delighted_
here's a thought that someone has probably had before and I definitely don't want to implement myself: can we handle the inbalance in an ensemble method by sampling most of the trues, but a random set of the falses? so that the whole ensemble does use the full set of falses, but each tree has closer to balanced data?
I am sure this is super naive in some way, but I'd love to hear what folks think, and , if this is a thing already, what it's called
With between 80% and 90% of #bigdata having an unstructured format, less than 20% of organizations report tapping this valuable resource (Harbert, 2021). Be more than a statistic. Use #BDE
Examine the capabilities and tools of big #data analytics systems, learn about #xml and its relationship with data, learn exciting systems design implementations from distinct industries, and much more! In store now
https://datatofu.wordpress.com
Additional Tags: #python #pydata #rstats #linux #datascience #ai
I gave a talk last year on getting started with APIs for data scientists. For some reason, I've only just got round to posting it on my blog.
https://blog.sellorm.com/2024/12/16/apis-for-ds/
#rstats #pydata #dataNerdFriendsOfAllFlavors
I'm building a binary classification model, and the data is really unbalanced (less than 2% of the data is in the class I want to predict)
tell me all your tips and tricks for dealing with data like this! What's your favorite model type to use in this case? Do you resample the data to change the balance?
I spent the last two days coding bepp, my first #Python project.
Its use case that is so specific I think nobody else will ever use it except me.
The tool is meant to clean up and merge together transaction summaries from Banca Etica and PayPal, exporting them in a simple #CSV.
Even though it’s a tiny silly script, I am very proud of it and I feel that I could create anything I set my mind to, now!
Thanks to my Introduction to Data Science course, that finally made me start learning Python with the time and dedication it deserves (my project for the course is very interesting too, will post about it in a few days).
Boss: loved the map you did of the world's mountains and volcanos yesterday
Me: sweet
Boss: but I need all the rivers on there, too, still a single spread
Me: the only library on #pypi that can do that has a CVE
Adrien: hold my beer (1829)
www.davidrumsey.com/luna/servlet...
#databs #rstats #pydata
Tableau comparatif et Figure d...
My first #Python package alive on PyPi. seekwellpandas is a simple extension for more intuitive, SQL-like queries in #pandas.
```
import pandas as pd
import seekwellpandas
df = pd.DataFrame({
'A': [1, 2, 3, 4],
'B': ['a', 'b', 'a', 'b'],
'C': [10, 20, 30, 40]
})
df.select('A', 'B')
```
Let me know what you think!
My #introduction:
I'm a healthcare-focused data scientist working primarily with #python. I am passionate about protecting patients' rights while advancing science.
I also love to bike, hike, and spend time with my 2 adorable rescue Siamese cats.
Gratitude is a guiding principle of mine, so thank you for hosting (in every sense) this space for us, @nova!
#healthcare #HealthTech #ClinicalTrial #DataScience #MachineLearning #NLP #pydata
#bike #BikeTooter #cycling #hike #cats ¯\_(ツ)_/¯
