Learn how to summarize any text and extract keywords. I’ve explained the concept and shown the gensim implementation! #nlp #gensim #machinelearning For more videos please subscribe – http://bit.ly/normalizedNERD Support me if you can ❤️ https://www.paypal.com/paypalme2/suji04 https://www.buymeacoffee.com/normalizednerd NLP playlist – https://www.youtube.com/playlist?list=PLM8wYQRetTxCCURc1zaoxo9pTsoov3ipY Source Code – https://github.com/Suji04/NormalizedNerd/blob/master/Introduction%20to%20NLP/Summarization%20%26%20Keyword%20Extraction.ipynb Project Gutenberg – https://www.gutenberg.org/files/2852/2852-h/2852-h.htm#chap15 Facebook – https://www.facebook.com/nerdywits/ Instagram – https://www.instagram.com/normalizednerd/ Twitter – https://twitter.com/nomalized_nerd
Text summarization is the process of creating a short, accurate, and fluent summary of a longer text document. It is the process of distilling the most important information from a source text. Automatic text summarization is a common problem in machine learning and natural language processing (NLP). Automatic text summarization methods are greatly needed to address the ever-growing amount of text data available online to both better help discover relevant information and to consume relevant information faster. 🔊 Watch till last for a detailed description 01:21 What is text summarization? 05:19 Installing the packages 15:10 Sentence tokenization 👇👇👇👇👇👇👇👇👇👇👇👇👇👇 ✍️🏆🏅🎁🎊🎉✌️👌⭐⭐⭐⭐⭐ ENROLL in My Highest Rated Udemy Courses to 🔑 Unlock Data Science Interviews 🔎 and Tests 📚 📗 NLP: Natural Language Processing ML Model Deployment at AWS Build & Deploy ML NLP Models with Real-world use Cases. Multi-Label & Multi-Class Text Classification using BERT. Course Link: https://bit.ly/bert_nlp 📊 📈 Data Visualization in Python Masterclass: Beginners to Pro Visualization in matplotlib, Seaborn, Plotly & Cufflinks, EDA on Boston Housing, Titanic, IPL, FIFA, Covid-19 Data. Course Link: https://bit.ly/udemy95off_kgptalkie 📘 📙 Natural Language Processing (NLP) in Python for Beginners NLP: Complete Text Processing with Spacy, NLTK, Scikit-Learn, Deep Learning, word2vec, GloVe, BERT, RoBERTa, DistilBERT Course Link: https://bit.ly/intro_nlp . 📈 📘 2021 Python for Linear Regression in Machine Learning Linear & Non-Linear Regression, Lasso & Ridge Regression, SHAP, LIME, Yellowbrick, Feature Selection & Outliers Removal. You will learn how to build a Linear Regression model from scratch. Course Link: https://bit.ly/regression-python 📙📊 2021 R 4.0 Programming [More]