TechLearn India
Login
TechLearn India/Intro to Deep Learning
Buy now

  • ₹3,749

Intro to Deep Learning

  • Course
  • 22 Lessons


Use Jupyter & Learn Tokenization Working with a NLP Pipeline Regular Expressions & Statistics to uncover insights and Create NLP & Speech to text with CNNs Solutions

Enroll now

Learn Now

Run Demo, on Online IDE.
Try for Free

Contents

Introduction to Deep Learning

What You Will Learn


Access and Use the Built-in Corpora of NLTK

Advance your programming skills and refine your ability to work with messy, complex NTLK Funtioning.
Tokenization,Working with a NLP Pipeline,Regular Expressions & Regular Expressions used in Tokenizing.
Course Context
deep learning.pdf
How to Install Jupyter Notebook on your System.pdf

Unit-1 Access and Use the Built-in Corpora of NLTK (Natural Language Toolkit).

Learn how to use the Built-in Corpora of NLTK
Walkthrough_Section 1-1_Access and Use the Built-in Corpora of NLTK.ipynb
Walkthrough_Section 1-2_Loading a Corpus.ipynb
Walkthrough_Section 1-4_Example of a Lexical Resource.ipynb
Walkthrough_Section 1-3_Example of a Conditional Frequency Distribution.ipynb

Unit-2 Working with NLP Pipeline

Unit- 2

2-1_Working with a NLP Pipeline 
2-2_Tokenization 
2-3_Regular Expressions
2-4_Regular Expressions used in Tokenizing 
Walkthrough_Section 2-1_Working with a NLP Pipeline.ipynb
Walkthrough_Section 2-2_Tokenization.ipynb
Walkthrough_Section 2-3_Regular Expressions.ipynb
Walkthrough_Section 2-4_Regular Expressions used in Tokenizing.ipynb

Unit-3 DEMONSTRATING HOW TO BUILD APPLICATION IN PYTHON

UNIT-3
  • Naive Bayes Text Classsification
  • Implementation of Age Prediction Application
  • Implementation of Document Classifier Application
DEMONSTRATING HOW TO BUILD APPLICATION IN PYTHON
Walkthrough_Section 3.1_Naive Bayes Text Classification.ipynb
Walkthrough_Section 3.3_Document Classifier Applicatoin.ipynb
Walkthrough_Section 3.2_Age Prediction Application.ipynb

Unit-4 Chunking, Chinking in Python

UNIT-4
Chunking in Python NLTK
Chinking in Python NLTK

Walkthrough_Section 4.2_Chunking in Python NLTK.ipynb
Walkthrough_Section 4.3_Chinking in Python NLTK.ipynb

Unit-5 BUILDING SPEECH TO TEXT USING VARIOUS METHODS

BUILDING SPEECH TO TEXT USING VARIOUS METHODS

  • Python Speech Recognition Module
  • Speech to text with recurrent neural networks
  • Speech to text with convolutional neural networks (part1)
  • Speech to text with convolutional neural networks (part2)
Speech to text with recurrent neural networks.ipynb
Walkthrough_Section 5.1_Python Speech Recognition Module.ipynb
Walkthrough_Section 5.2_Speech to text with recurrent neural networks.ipynb
Walkthrough_Section 5.3_Speech to text with convolutional neural networks (part 1).ipynb
Walkthrough_Section 5.4_Speech to text with convolutional neural networks (part 2).ipynb