Learn over 15+ tools including TextBlob,NLTK,Spacy,Flair, for performing NLP Projects
What you'll learn
- Understand Natural Language Processing Concepts and its implementation in code
- Learn the tools for fetching data from Text Files,PDF,API,etc
- Text cleaning and pre-processing for NLP projects
- Stylometry in Python
- Perform Sentiment Analysis with TextBlob,Vader,Flair and Machine Learning and more
- Keyword Extraction using Yake,Rake,Textrank and Spacy
- Build NLP Applications eg Document Redaction,Text Classification,Sentiment Analysis, Stylometry,Author Attribution,etc
- Explore various tools used in an End to End NLP Project
- NLP with Spacy,Flair,TextBlob,NLTK,etc
- Basic understanding of Python programming language
- Determination and Desire to Learn new things
Do you know that there are over 7000 human languages in the world? Is it even possible to empower machines and computers to be able to understand and process these human languages? In this course we will be exploring the concept and tools for processing human (natural) language in python.
Hence if you are interested in Natural Language Processing Projects and are curious on how sentiment analysis,text classification,summarization,and several NLP task works? Then this course is for you.
Natural Language Processing is an exciting field of Data Science but there are a lot of things to learn to keep up. New concepts and tools are emerging every day. So how do you keep up ?
In this course on Awesome Natural Language Processing Tools In Python we will take you on a journey on over 15+ tools you need to know and be aware of when doing an NLP project in a format of a workflow.
Tools and technologies are always changing but workflows and systems remain for a long time hence we will be focusing on the workflow and the tools required for each. The course approaches Natural Language Processing via the perspective of using a workflow or simple NLP Project Life Cycle.
By the end of this exciting course you will be able to
- Fetch Textual Data From most document(docx,txt,pdf,csv),website etc
- Clean and Preprocess unstructured text data using several tools such as NeatText,Ftfy,Regex,etc
- Understand how tokenization works and why tokenization is important in NLP
- Perform stylometry in python to identify and verify authors
- NLP with Spacy,TextBlob,Flair and NLTK
- Learn how to do text classification with Machine Learning,Transformers, TextBlob ,Flair,etc
- Build some awesome NLP apps using Streamlit
- Perform Sentiment Analysis From Scratch and with Several NLP Packages
- Build features from textual data- Word2Vec,FastText,Tfidf
- And many more
Join us as we explore the world of Natural Language Processing.
See you in the Course,Stay blessed.
Tips for getting through the course
- Please write or code along with us do not just watch,this will enhance your understanding.
- You can regulate the speed and audio of the video as you wish,preferably at -0.75x if the speed is too fast for you.
- Suggested Prerequisites is understanding of Python
- This course is NOT a 'Theoretical Introduction to NLP' nor 'Advanced Concepts in NLP' although we try our best to cover some concepts for the beginner and the pro. Rather it is about the tools used for NLP Project workflow.
- Beginner Python Developers curious about Natural Language Processing
- Data Scientist and Developers
- Forensic Linguistics
- Everyone interested in NLP and Text Analysis