mani neomatrix369

## dl-resources.md

      
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                Deep Learning Hands-On Series with Eric Schles 
              
          
    Deep Learning Hands-On Series with Eric Schles

05/22 - Deep Learning Hands-On Series - Data Exploration and API First Design 🎥
05/29 - Deep Learning Hands-On Series - Model Tuning 🎥
06/05 - Deep Learning Hands-On Series - Monitoring [cancelled]
Resources

Notebooks


## know-your-gpus.md

      
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                neomatrix369
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              December 14, 2023 02:44
            
              
                Know your GPUs
              
          
    Commands on Linux to gather information related to GPUs

Below is a list of commands and resources that work on Linux (some need installation of packages), would love to welcome contributions for the same for MacOSX and Windows platforms too. Please share and contribute back.
Please run the below in both vagrant, docker and other container environments and share your experiences with us!
About me: http://neomatrix369.wordpress.com/about, my blogs: http://neomatrix369.wordpress.com/
Get Hardware Details


## xgb_quantile_loss.py
import numpy as np


def xgb_quantile_eval(preds, dmatrix, quantile=0.2):
    """
    Customized evaluational metric that equals
    to quantile regression loss (also known as
    pinball loss).

    Quantile regression is regression that

## plag.py
from nltk.corpus import wordnet
from nltk.tokenize import word_tokenize
from random import randint
import nltk.data

# Load a text file if required
text = "Pete ate a large cake. Sam has a big mouth."
output = ""

# Load the pretrained neural net
	import numpy as np


	def xgb_quantile_eval(preds, dmatrix, quantile=0.2):
	"""
	Customized evaluational metric that equals
	to quantile regression loss (also known as
	pinball loss).

	Quantile regression is regression that
	from nltk.corpus import wordnet
	from nltk.tokenize import word_tokenize
	from random import randint
	import nltk.data

	# Load a text file if required
	text = "Pete ate a large cake. Sam has a big mouth."
	output = ""

	# Load the pretrained neural net