Natural Language Processing, Deploy on Cloud(AWS) [Hindi] | Data Science Online Course by Udemy

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Natural Language Processing (NLP), Machine Learning, Spam Filter, Sentiment Analysis [Python][Hindi]

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

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 – StepsChapter – Setup Environment – Installing Anaconda, how to use Spyder and Jupiter Notebook- Installing LibrariesChapter – Creating Environment on cloud (AWS)- Creating EC2, connecting to EC2- Installing libraries, transferring files to EC2 instance, executing python scriptsChapter – Data Analysis and Data Cleaning- Drawing various kinds of graph to understand the trend- Regular Expression for data cleaningChapter – Text PreprocessingBelow Text Preprocessing Techniques- Tokenization, Stop Words Removal, N-Grams- Stemming, Word Sense DisambiguationChapter – Text Preprocessing – Python CodeBelow Text Preprocessing Techniques with Python code- Tokenization, Stop Words Removal, N-Grams, Stemming, Word Sense Disambiguation- Count Vectorizer, Tfidf Vectorizer. Hashing VectorChapter – Vectorizing- Count Vectorizer- Tfidf Vectorizer- Hashing VectorChapter – 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 MatrixChapter – Spam Filter – Concept with Python CodeChapter – Sentiment Analysis- Concept with Python CodeChapter: 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 serverChapter – Summarizing Article – Concept with Python CodeChapter: UnSupervised Learning: Clustering- Partitioning Algorithm: K-Means Algorithm- Random Initializing Trap- Measuring UnSupervised Clusters Performace – Elbow MethodChapter – Article Classification- Concept with Python Code

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