Course Content
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Day 01 - Module 1 Python Refresher 0/4
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ListsLecture1.1
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DictionariesLecture1.2
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Loops and ConditionalsLecture1.3
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FunctionsLecture1.4
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Module 2 NLTK and the Basics 0/9
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Overview – The Natural Language Tool KitLecture2.1
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Counting TextLecture2.2
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Example – Words Per Sentence TrendsLecture2.3
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Frequency DistributionLecture2.4
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Conditional Frequency DistributionLecture2.5
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Example – Informative WordsLecture2.6
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BigramsLecture2.7
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Overview – Regular ExpressionsLecture2.8
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Regular Expression PracticeLecture2.9
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Day 02 - Module 1 Tokenization , Tagging, Chunking 0/8
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Overview – TokenizationLecture3.1
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TokenizationLecture3.2
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NormalizingLecture3.3
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Part of Speech TaggingLecture3.4
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Example – Multiple Parts of SpeechLecture3.5
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Example – ChoicesLecture3.6
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ChunkingLecture3.7
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Named Entity RecognitionLecture3.8
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Module 2 Custom Sources 0/8
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Overview – Character EncodingLecture4.1
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Text FileLecture4.2
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HTMLLecture4.3
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URLLecture4.4
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CSV FileLecture4.5
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ExportingLecture4.6
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NLTK ResourcesLecture4.7
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Example – Remove StopwordsLecture4.8
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Module 3 Projects 0/6
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Sentiment Analysis IntroLecture5.1
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Basic Sentiment AnalysisLecture5.2
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Gender Prediction IntroLecture5.3
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Gender PredictionLecture5.4
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TF-IDF IntroLecture5.5
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TF-IDFLecture5.6
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Example – Choices