Based on 2018 HackerRank's Developer survey, #Javascript #Java #Python stand out as the top 3 expected Programming languages but what's next is more important. That's being Language Agnostic!
This is very important especially in #DataScience and #MachineLearning where we always put R
The screenshot is from a Gender-focused #Kaggle Kernel I did sometime back : https://lnkd.in/fXCDHjv
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
This is very important especially in #DataScience and #MachineLearning where we always put R
vs Python, but with market expecting Language Agnostic Developers, It's good to have both the languages at your disposal. The screenshot is from a Gender-focused #Kaggle Kernel I did sometime back : https://lnkd.in/fXCDHjv
✴️ @AI_Python_EN
❇️ @AI_Python
🗣 @AI_Python_arXiv
Step 1: pip install ludwig
Step 2: Download a csv dataset
Step 3: Create a model definition yaml file to specify input and output features
Step 4: Run ludwig experiment --data_csv path_to_csv --model_definition_file model_definition.yaml
Step 5: Receive a high accuracy model for rating a clothing item from a Kaggle dataset or any other dataset
Step 6: WOW! This is almost like making noodles in 2 minutes!
A few years ago, when I helped establish a new HP office in Braunschweig, Germany for a newly acquired team, it was a building located on a street called Ludwig Strasse and my German GPS confused me so much that I wished I had a self driving German car to locate this building :) BTW, almost every other street in Germany is named Ludwig something, right Simon Winkelbach ? :)
Curiosly enough, Uber names its self-driving deep learning model design framework Ludwig and I am immediately reminded of LudwigStrasse in Braunschweig. I decided to give this Uber Ludwig a self-driving spin and it reminded me of Microsoft AzureML studio (which is a more visual design framework of course)
https://lnkd.in/gijwygv
#deeplearning
#kaggle
✴️ @AI_Python_EN
Step 2: Download a csv dataset
Step 3: Create a model definition yaml file to specify input and output features
Step 4: Run ludwig experiment --data_csv path_to_csv --model_definition_file model_definition.yaml
Step 5: Receive a high accuracy model for rating a clothing item from a Kaggle dataset or any other dataset
Step 6: WOW! This is almost like making noodles in 2 minutes!
A few years ago, when I helped establish a new HP office in Braunschweig, Germany for a newly acquired team, it was a building located on a street called Ludwig Strasse and my German GPS confused me so much that I wished I had a self driving German car to locate this building :) BTW, almost every other street in Germany is named Ludwig something, right Simon Winkelbach ? :)
Curiosly enough, Uber names its self-driving deep learning model design framework Ludwig and I am immediately reminded of LudwigStrasse in Braunschweig. I decided to give this Uber Ludwig a self-driving spin and it reminded me of Microsoft AzureML studio (which is a more visual design framework of course)
https://lnkd.in/gijwygv
#deeplearning
#kaggle
✴️ @AI_Python_EN