amitness

Group 0

• How to Make Manual Predictions for ARIMA Models with Python
• How to Make Out-of-Sample Forecasts with ARIMA in Python
• How to Model Residual Errors to Correct Time Series Forecasts with Python
• How to Tune ARIMA Parameters in Python
• Sensitivity Analysis of History Size to Forecast Skill with ARIMA in Python

Group 1

• About
• Terms of Service

amitness

title,label
"15 Highly Important Questions About Adulthood, Answered By Michael Ian Black",1
250 Nuns Just Cycled All The Way From Kathmandu To New Delhi,1
"Australian comedians ""could have been shot"" during APEC prank",0
Lycos launches screensaver to increase spammers' bills,0
Fußball-Bundesliga 2008–09: Goalkeeper Butt signs with Bayern Munich,0
"In Afghanistan, Soldiers Bridge 2 Stages of War",0
"After Fleeing North Korea, an Artist Parodies Its Propaganda",0
Lessons (or Not) When a Start-Up Misses the Mark,0
Court Issues Order Against 3 Car-Warranty Calling Firms,0

amitness

Writing a Research Proposal

Objectives (Motivation)

• What will be solved?
• What will be achieved?
• Why is this research important?
  • Scientific
  • Application
  • Society

amitness

import pandas as pd
from deepmoji import DeepMoji

# Instantiate the Emoji Model
emoji_model = DeepMoji()

# Read a file containing user opinions
df = pd.read_csv('https://bit.ly/2VbfNiM')
                 
# Predict the emojis for the open-ended text

amitness

import string
from wordcloud import WordCloud
from collections import Counter
import matplotlib.pyplot as plt

class EmojiCloud:
    def __init__(self,
                 font_path='Symbola.ttf',
                 color='yellow'):
        self.font_path = font_path

amitness

import string
from wordcloud import WordCloud
from collections import Counter
import matplotlib.pyplot as plt

class EmojiCloud:
    def __init__(self,
                 font_path='Symbola.ttf',
                 color='yellow'):
        self.font_path = font_path

amitness

emoji_cloud = EmojiCloud(font_path='./Symbola.ttf', color='yellow')
emoji_cloud.generate(emojis)

amitness

pip install git+https://github.com/nexxt-intelligence/DeepMoji@tf-keras
pip install wordcloud matplotlib

amitness

from zipfile import ZipFile

for annotator, subset in annotation_df.groupby('annotator'):
    with ZipFile(f'{annotator}.zip', 'w') as z:
        for path in subset['image_path']:
            z.write(path, os.path.basename(path))

amitness

# Download button

st.download_button(
     label="Download sample file here",
     data=sample_file,
     file_name='sample_data.csv',
     mime='text/csv',
 )