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Data-Science-Learning-Path
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Grade
Name
Complexity
Churn
Issues
A
Data Scientist Career Path\12. Foundations of Machine Learning Unsupervised Learning\1. KMeans\10. evaluation.py
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Data Scientist Career Path\11. Foundations of Machine Learning Supervised Learning\3. Multiple\8. evaluate.py
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Data Scientist Career Path\12. Foundations of Machine Learning Unsupervised Learning\1. KMeans\2. visualize.py
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Data Scientist Career Path\10. Natural Language Processing\4. TFIDF\6. review.py
 1 2
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Data Scientist Career Path\10. Natural Language Processing\5. Word Embeding\2. vector.py
 1 6
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Data Scientist Career Path\12. Foundations of Machine Learning Unsupervised Learning\2. KMeans++\1. intro.py
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Data Scientist Career Path\12. Foundations of Machine Learning Unsupervised Learning\2. KMeans++\2. poor.py
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Data Scientist Career Path\10. Natural Language Processing\5. Word Embeding\3. what.py
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Data Scientist Career Path\10. Natural Language Processing\2. Text Processing\6. lemma.py
 1 3
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Data Scientist Career Path\12. Foundations of Machine Learning Unsupervised Learning\1. KMeans\8. new.py
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Data Scientist Career Path\10. Natural Language Processing\2. Text Processing\8. review.py
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Data Scientist Career Path\10. Natural Language Processing\5. Word Embeding\4. distance.py
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Data Scientist Career Path\10. Natural Language Processing\1. Getting Started\3. bag.py
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Data Scientist Career Path\10. Natural Language Processing\1. Getting Started\8. advance.py
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Data Scientist Career Path\11. Foundations of Machine Learning Supervised Learning\4. Classification\2. Regression\3. scikit.py
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Data Scientist Career Path\10. Natural Language Processing\5. Word Embeding\7. gensim.py
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Data Scientist Career Path\11. Foundations of Machine Learning Supervised Learning\5. Evaluating\1. accuracy.py
 1 1
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Data Scientist Career Path\11. Foundations of Machine Learning Supervised Learning\5. Evaluating\2. recall.py
 1 1
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Data Scientist Career Path\11. Foundations of Machine Learning Supervised Learning\2. Regression\1. Distance\1. point.py
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Data Scientist Career Path\11. Foundations of Machine Learning Supervised Learning\5. Evaluating\3. precision.py
 1 1