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Natural Language Processing, Deploy on Cloud(AWS) [Hindi]

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Course Instructor:

Rishi Bansal

Course Language:

English

Course Descreption:

Natural Language Processing, Deploy on Cloud(AWS) [Hindi]

Go to Offer

This course offers a fundamental understanding of NLP. Anyone can go for this course. Prior understanding of Machine Learning is nice to have. However, for individuals who don;t know Machine Learning, I have added sections for Machine Learning. Text Processing like Tokenization, Stop Words Removal, Stemming, several types of Vectorizers, WSD, and so on are defined intimately with python code. Also distinction between CountVectorizer and Hashing in Spam Filter.

Below Topics are lined

Chapter – Introduction to Natural Language Processing (NLP)

– NLP?

– NLP functions

– Machine Learning – Steps

Chapter – Setup Environment

– Installing Anaconda, use Spyder and Jupiter Notebook

– Installing Libraries

Chapter – Creating Environment on cloud (AWS)

– Creating EC2, connecting to EC2

– Installing libraries, transferring recordsdata to EC2 occasion, executing python scripts

Chapter –  Data Analysis and Data Cleaning

– Drawing varied sorts of graph to grasp the pattern

– Regular Expression for knowledge cleansing

Chapter – Text Preprocessing

Below Text Preprocessing Techniques

– Tokenization, Stop Words Removal, N-Grams

– Stemming, Word Sense Disambiguation

Chapter – Text Preprocessing – Python Code

Below Text Preprocessing Techniques with Python code

– Tokenization, Stop Words Removal, N-Grams, Stemming, Word Sense Disambiguation

– Count Vectorizer, Tfidf Vectorizer. Hashing Vector

Chapter – Vectorizing

– Count Vectorizer

– Tfidf Vectorizer

– Hashing Vector

Chapter – Machine Learning

– What is Machine Learning and its Types?

– Supervised Learning

– Simple Linear Regression

– Regression Model Performance – R-Square

– Logistic Regression

– Okay-Nearest Neighbours

– Naive Bayes

– Classification Model Performance – Confusion Matrix

Chapter  – Spam Filter

– Concept with Python Code

Chapter  – Sentiment Analysis

– Concept with Python Code

Chapter: Deploy Machine Learning Model utilizing Flask on AWS

– Understanding the stream

– Serverside and Clientside coding, Setup Flask on AWS, sending request and getting response again from flask server

Chapter  – Summarizing Article

– Concept with Python Code

Chapter: UnSupervised Learning: Clustering

– Partitioning Algorithm: Okay-Means Algorithm

– Random Initializing Trap

– Measuring UnSupervised Clusters Performace

– Elbow Method

Chapter  – Article Classification

– Concept with Python Code

Instructors: Rishi Bansal

 

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