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

 Buy Now
  

Price: 19.99$

This course provides a basic understanding of NLP. Anyone can opt for this course. Prior understanding of Machine Learning is good to have. However, for those who don;t know Machine Learning, Ihave added sections for Machine Learning. Text Processing like Tokenization, Stop Words Removal, Stemming, different types of Vectorizers, WSD, etc are explained in detail with python code. Application of NLP like Spam Filter, Sentiment Analysis, Auto-Summarizing Article and Article Classification implemented in python. Below Topics are covered Chapter – Introduction to Natural Language Processing (NLP)- NLP?- NLP applications- Machine Learning – Steps Chapter – Setup Environment – Installing Anaconda, how to use Spyder and Jupiter Notebook- Installing Libraries Chapter – Creating Environment on cloud (AWS)- Creating EC2, connecting to EC2- Installing libraries, transferring files to EC2 instance, executing python scripts Chapter – Data Analysis and Data Cleaning- Drawing various kinds of graph to understand the trend- Regular Expression for data cleaning 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- K-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 using Flask on AWS- Understanding the flow- Serverside and Clientside coding, Setup Flask on AWS, sending request and getting response back from flask server Chapter – Summarizing Article – Concept with Python Code Chapter: Un Supervised Learning: Clustering- Partitioning Algorithm: K-Means Algorithm- Random Initializing Trap- Measuring Un Supervised Clusters Performace – Elbow Method Chapter – Article Classification- Concept with Python Code