Natural Language Processing with Python

Learn NLP concepts with practical implementation using Python, TensorFlow, PyTorch, spaCy, gensim
What you'll learn
Concepts of Natural Language Processing and its Applications across various domains
Pratical implementation of Natural Language Processing Technqiues using Python, TensorFlow, PyTorch, Transformers, spaCy and gensim libraries
Understand how to approach and solve NLP problems
Understand how to use advanced NLP models like BERT
Requirements
Basic knowledge of python
Basic knolwedge of machine learning
Description
In this course you will be learning about Natural Language Processing (NLP) from an experienced professional. Giving machines the capacity to find meaning in unstructured data pulled from natural language holds notable promise. By 2025, the global NLP market is expected to reach over $34 billion, growing at a CAGR of 21.5% and there would be high demand for NLP skills. In this course I cover length and breadth of topics in NLP. I explain NLP concepts in a simple way along with practical implementation in Python using libraries like NLTK, spaCy, TensorFlow and PyTorch. I also discuss various topics like text pre-processing, text classification, text summarization, topic modelling and word embeddings. I also cover NLP applications in various domains like healthcare, finance. I am sure this course should help you in getting started and also become proficient in NLP

In this video course you will learn the following about Natural Language Processing:
Introduction to NLP
Its Applications in domains like finance and healthcare
Stemming and Lemmatimzation with NLTK and spaCy
TF-IDF, Bag of Words Representation
Named Entity Recognition with spaCy in python
Custom Named Entity Recognition using spaCy v3 library
Word2Vec model and custom word2vec model in python
Exploratory data analysis on text dataset using python
Text Clustering
Text Classification with Neural network using Tensorflow in Python
Text Classification with Convolutional Neural Network( CNN) using Tensorflow in Python
Text Classification with Long Short Term memory( LSTM) networks using Tensorflow in Python
Text Classification using PyTorch library
Text Classification using BERT Transformers
Text Classification using spaCy v3 library
Zero shot text classification using HuggingFace
LDA topic modelling
Top2Vec Topic Modelling
BERTopic Topic Modelling
Extractive Text Summarization using gensim and python
Abstractive Text Summarization using Google PEGASUS
Extractive Question Answering with HuggingFace
Aspect Based Sentiment Analysis
HayStack Question Answering Demo

For advanced NLP content check out my Youtube Channel


Who this course is for:
Beginners who want to learn about Natural Language Processing in a practical way from an experienced professional
Beginner python developers who are curious to learn about natural language processing

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