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machine-learning-library

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.

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rasa
ortsaCniveK
ortsaCniveK commented Apr 15, 2020

Description of Problem:
Had to add a Facebook messenger channel integration into a bot I spun up and found the Facebook Messenger docs lacking a bit especially on the special response template keys quick_replies and elements; I had to read through the Facebook channel source to figure out what was allowed/disallowed.

Overview of the Solution:
FB Messenger docs updated with additio

Shotgun167
Shotgun167 commented May 1, 2019

I have some values in slots that are surrounded by curly braces and are meant to be returned as is. Instead, the trailing brace is being stripped. "${website}" becomes "${website". I have training examples where the whole "${website}" is included. Is there a way to change this behavior?

kartikdutt18
kartikdutt18 commented Mar 13, 2020

This is a good first issue and will help new contributors to get familiar with the codebase. Also This issue doesn't aim to add all Metrics to mlpack since each metric would have to be maintained, this aims to add metrics that either I find essential (or have used a couple of time) or those metrics which are very common.
List of metrics that can be added include:

  1. IoU and meanIoU
StrikerRUS
StrikerRUS commented Oct 18, 2019

I'm sorry if I missed this functionality, but CLI version hasn't it for sure (I saw the related code only in generate_code_examples.py). I guess it will be very useful to eliminate copy-paste phase, especially for large models.

Of course, piping is a solution, but not for development in Jupyter Notebook, for example.

ghk829
ghk829 commented May 30, 2019

I run this code

import os
os.environ['is_test_suite']="True" # this is writen due to bug for multiprocessing and pickling I issued. #426 
from auto_ml import Predictor
from auto_ml.utils import get_boston_dataset
from auto_ml.utils_models import load_ml_model

# Load data
df_train, df_test = get_boston_dataset()

# Tell auto_ml which column is 'output'
# Also note columns t
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