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NLP with AI

NLP with AI - Basic

Duration in Hours (4 Hours session) : 60

Duration in Days: 15

DS05 NLP with AI

Course Code: NLPAI20CS

40 Hours of Theory

20 Hours of Assignment (Lab)

Natural Language Processing In AI (NLP)

  1. Introduction
  2. Spacy Setup & Overview
  3. Spacy Basics
  4. Tokenization
  5. Stemming
  6. Lemmatization
  7. Stop Words
  8. Phrase Matching & Vocabulary
  1. Introduction
  2. Count Vectorizer
  3. Vector Similarity
  4. TF-IDF
  5. Word-to-Index Mapping
  6. Neural Word Embeddings
  7. Text Summarization
  1. Classification Matrix
  2. Confusion Matrix
  3. Scikit-Learner Primer
  4. Text Feature Extraction
  5. Text Summarization using Vectors
  6. TextRank
  1. Semantics and Word Vectors with Spacy
  2. Latent Semantic Analysis
  3. Latent Semantic Indexing
  4. Singular Value Decomposition
  5. Sentiment Analysis Overview
  6. Sentiment Analysis with NLTK
  1. The Basic Perceptron Model
  2. Introduction to Neural Networks
  3. Keras Basics
  4. Neuron Introduction
  5. Fitting a Line
  6. Classification Code Preparation
  7. Text Classification in Tensorflow
  8. How does a model learn?
  1. Forward Propagation
  2. Geometrical Picture
  3. Activation Functions
  4. Multiclass Classification
  5. Text Classification ANN in Tensorflow
  6. Text Preprocessing in Tensorflow
  7. Embeddings
  8. CBOW
  1. What is Convolution?
  2. Pattern Matching
  3. Weight Sharing
  4. CNNs for Text
  5. CNN for NLP in Tensorflow
  1. Simple RNN / Elman Unit
  2. RNNs: Paying Attention to Shapes
  3. GRU and LSTM
  4. RNN for Text Classification in Tensorflow
  5. Named Entity Recognitin (NER) in Tensorflow
  1. Decent Python programming skills
  2. Math parts: Linear algebra and probability are helpful
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