About the course

ARTIFICIAL INTELLIGENCE 
 
➢ MODULE 1: AI INTRODUCTION  
    • Perceptron 
    • AI Applications 
 
 DEEP LEARNING 
    ➢ MODULE 2: DEEP LEARNING ALGORITHMS  
    • CNN – Convolutional Neural Network 
    • RNN – Recurrent Neural Network 
    • ANN – Artificial Neural Network 
     
 INTRODUCTION TO NLP  
    ➢ MODULE 3: NLP 
    • Text Pre-processing 
    • Noise Removal 
    • Lexicon Normalization 
    • Lemmatization 
    • Stemming 
    • Object Standardization 
     
➢ MODULE 4: TEXT TO FEATURES (FEATURE ENGINEERING)  
    • Part of Speech Tagging 
    • Entity Parsing 
    • Named Entity Recognition 
    • Topic Modelling 
    • N-Grams 
    • TF – IDF 
    • Frequency / Density Features 
    • Word Embedding’s