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    Natural Language Processing (NLP) in Python with 8 Projects

    BY
    Udemy

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    Mode

    Online

    Fees

    ₹ 499 3499

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study
    Mode of Delivery Video and Text Based

    Course and certificate fees

    Fees information
    ₹ 499  ₹3,499
    certificate availability

    Yes

    certificate providing authority

    Udemy

    The syllabus

    Welcome

    • Course Overview
    • Reviews UPDATE
    • Introduction to NLP
    • Course FAQs

    Installation & Setup

    • Course Installation
    • Local Installation Steps
    • Links to Notebooks (As taught in Lectures)
    • Links to Notebooks (More explanatory notebook for refrence)

    Basics of Natural Language Processing

    • Section : Introduction
    • Tokenization Basic Part - 1
    • Tokenization Basic Part - 2
    • Tokenization Basic Part - 3
    • Stemming & Lemmatization - 1
    • Stemming & Lemmatization - 2
    • Stop Words
    • Vocabulary and Matching Part - 1
    • Vocabulary and Matching Part - 2 (Rule Based)
    • Vocabulary and Matching Part - 3 (Phrase Based)
    • Parts of Speech Tagging
    • Named Entity Recognition
    • Sentence Segmentation
    • NLP Basics

    Project 1 : Spam Message Classification

    • Business Problem & Dataset
    • Data Exploration & Preprocessing
    • Split Data in Training & Testing
    • Apply Random Forest
    • Apply Support vector Machine (SVM)
    • Predict Testing Data both model
    • Quiz

    Project 2 : Restaurant Review Prediction (Good or bad)

    • Business Problem
    • Cleaning Text Data with NLTK - 1
    • Cleaning Text Data with NLTK - 2
    • Bag of Word Model
    • Apply Naive Bayes Algorithm

    Project 3 : IMDB, Amazon and Yelp review Classification

    • Review Classification Part -1
    • Review Classification Part - 2

    Project 4 : Automated Text Summarization

    • Importing the libraries and Dataset
    • Create Word Frequency Counter
    • Calculate Sentence Score
    • Extract summary of document

    Project 5 : Twitter sentiment Analysis

    • Setting up Twitter Developer application
    • Fetch Tweet from Tweeter server
    • Find Setiment from Tweets

    Deep Learning Basics

    • The Neuron
    • Activation Function
    • Cost Function
    • Gradient Descent and Back-Propagation

    Word Embeddings

    • Introduction to Word Embedding
    • Train Model for Embedding - I
    • Train Model for Embedding - II
    • Embeddings with Pretrained model
    • Word Embeddings

    Project 6 : Text Classification with CNN

    • Convolutional Neural Network Part 1
    • Convolutional Neural Network Part 2
    • Spam Detection with CNN - I
    • Spam Detection with CNN - II

    Project 7 : Text Classification with RNN

    • Introduction to Recurrent Neural Networks
    • Vanishing Gradient Problem
    • LSTM and GRU
    • Spam Detection with RNN

    Project 8 : Automatic Text Generation using TensorFlow, Keras and LSTM

    • Text Generation Part I
    • Text Generation Part II

    FastText Library for Text Classification

    • fasttext Installation steps [Video]
    • fasttext Installation steps [Text]
    • Virtual Box Installation
    • Create Linux Virtual Machine
    • Install fasttext library
    • Text Classification with Fasttext

    Data analysis with Numpy

    • Introduction to NumPy
    • Numpy Arrays Part 1
    • Numpy Arrays Part 2
    • Numpy Arrays Part 3
    • Numpy Indexing and Selection Part 1
    • Numpy Indexing and Selection Part 2
    • Numpy Operations

    Data analysis with Pandas

    • Pandas Introduction
    • Pandas Series
    • DataFrames Part 1
    • DataFrames Part 2
    • DataFrames Part 3
    • Missing Data
    • Groupby Method
    • Merging, Joining and Concatenating DataFrames
    • Pandas Operations
    • Reading and Writing Files in Pandas

    Data Visualization with Matplotlib

    • Matplotlib Part 1 - Functional Method
    • Matplotlib Part 1 - Object Oriented Method
    • Matplotlib Part 2 - Subplots Method
    • Matplotlib Part 2 - Figure size, Aspect ratio and DPI
    • Matplotlib Part 3
    • Matplotlib Part 4

    Appendix

    • Text File Processing - I
    • Text File Processing - II
    • Text File Processing - III
    • Text File Processing - IV
    • Working with PDF File - I

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