PDC4S:\IT\DATA SCIENCE AND MACHINE LEARNING\Practical Machine Learning, Twitter-API & Map Visualization\5. Your First Big Machine Learning Project Sentiment Analysis of Tweets |
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1. Introduction to Sentiment Analysis in Machine Learning.mp4 | 48,120 KB | 12/12/2021 3:34 AM |
1. Introduction to Sentiment Analysis in Machine Learning.srt | 5 KB | 12/12/2021 3:34 AM |
10. Step 2c Remove stop words (with Python).mp4 | 58,038 KB | 12/12/2021 3:34 AM |
10. Step 2c Remove stop words (with Python).srt | 5 KB | 12/12/2021 3:34 AM |
11. Code Step 2c Remove stop words.html | 2 KB | 12/12/2021 3:34 AM |
11.1 CreateSentimentModel.py | 2 KB | 12/12/2021 3:34 AM |
12. Step 3 Transform Data.mp4 | 149,717 KB | 12/12/2021 3:34 AM |
12. Step 3 Transform Data.srt | 12 KB | 12/12/2021 3:34 AM |
12.1 httpswww.nltk.orgapinltk.classify.html.html | 1 KB | 12/12/2021 3:34 AM |
13. Code Step 3 Transform Data.html | 3 KB | 12/12/2021 3:34 AM |
13.1 CreateSentimentModel.py | 2 KB | 12/12/2021 3:34 AM |
14. Step 4 Divide the dataset into training and testing set.mp4 | 69,508 KB | 12/12/2021 3:34 AM |
14. Step 4 Divide the dataset into training and testing set.srt | 6 KB | 12/12/2021 3:34 AM |
14.1 httpsdocs.python.org3libraryrandom.html.html | 1 KB | 12/12/2021 3:34 AM |
15. Code Step 4 Divide the dataset into training and test set.html | 3 KB | 12/12/2021 3:34 AM |
15.1 CreateSentimentModel.py | 3 KB | 12/12/2021 3:34 AM |
16. Step 5-6 Training and test the model.mp4 | 129,749 KB | 12/12/2021 3:34 AM |
16. Step 5-6 Training and test the model.srt | 11 KB | 12/12/2021 3:34 AM |
16.1 httpswww.nltk.orgapinltk.classify.html.html | 1 KB | 12/12/2021 3:34 AM |
17. Code Step 5-6 Training and test the model.html | 3 KB | 12/12/2021 3:34 AM |
17.1 CreateSentimentModel.py | 3 KB | 12/12/2021 3:34 AM |
18. Step 7 Save the pickle.mp4 | 102,613 KB | 12/12/2021 3:34 AM |
18. Step 7 Save the pickle.srt | 9 KB | 12/12/2021 3:34 AM |
18.1 httpsdocs.python.org3librarypickle.html.html | 1 KB | 12/12/2021 3:34 AM |
19. Code Step 7 Save the pickle.html | 3 KB | 12/12/2021 3:34 AM |
19.1 CreateSentimentModel.py | 3 KB | 12/12/2021 3:34 AM |
2. The Library you will use NLTK and download the datasets.mp4 | 44,926 KB | 12/12/2021 3:34 AM |
2. The Library you will use NLTK and download the datasets.srt | 5 KB | 12/12/2021 3:34 AM |
2.1 httpwww.nltk.org.html | 1 KB | 12/12/2021 3:34 AM |
3. Code Download the training data.html | 1 KB | 12/12/2021 3:34 AM |
4. Step 1 Gather the data (import the downloaded data in Python).mp4 | 65,741 KB | 12/12/2021 3:34 AM |
4. Step 1 Gather the data (import the downloaded data in Python).srt | 6 KB | 12/12/2021 3:34 AM |
5. Code Step1 Gather the data.html | 1 KB | 12/12/2021 3:34 AM |
5.1 CreateSentimentModel.py | 1 KB | 12/12/2021 3:34 AM |
6. Step 2a Clean the data (with Python).mp4 | 76,997 KB | 12/12/2021 3:34 AM |
6. Step 2a Clean the data (with Python).srt | 7 KB | 12/12/2021 3:34 AM |
7. Step 2a Clean the data.html | 1 KB | 12/12/2021 3:34 AM |
7.1 CreateSentimentModel.py | 1 KB | 12/12/2021 3:34 AM |
8. Step 2b Lemmatize the data (with Python).mp4 | 90,634 KB | 12/12/2021 3:34 AM |
8. Step 2b Lemmatize the data (with Python).srt | 7 KB | 12/12/2021 3:34 AM |
9. Code Step 2b Lemmatize words.html | 2 KB | 12/12/2021 3:34 AM |
9.1 CreateSentimentModel.py | 2 KB | 12/12/2021 3:34 AM |