NLP-Natural Language Processing in Python
NLP-Natural Language Processing in Python
Language,Python,Development,Data Science,Machine Learning
Lectures -234
Resources -3
Duration -23.5 hours
30-days Money-Back Guarantee
Get your team access to 9000+ top Tutorials Point courses anytime, anywhere.
Course Description
This course is designed to be your complete online resource for learning how to use Natural Language Processing with the Python programming language.
In the course, we will cover everything you need to learn in order to become a world-class practitioner of NLP with Python.
We'll start off with the basics, learning how to open and work with text and\u00a0PDF files with Python, as well as learning how to use regular expressions to search for custom patterns inside text files.
Afterward, we will begin with the basics of Natural Language Processing, utilizing the Natural Language Toolkit library for Python, as well as the state-of-the-art Spacy library for ultra-fast tokenization, parsing, entity recognition, and lemmatization of text.
We'll understand fundamental NLP concepts such as stemming, lemmatization, stop words, phrase matching, tokenization, and more!
Next, we will cover Part-of-Speech tagging, where your Python scripts will be able to automatically assign words in text to their appropriate part of speech, such as nouns, verbs, and adjectives, an essential part of building intelligent language systems.
We'll also learn about named entity recognition, allowing your code to automatically understand concepts like money, time, companies, products, and more simply by supplying text information.
Through state-of-the-art visualization libraries, we will be able view these relationships in real-time.
Then we will move on to understanding machine learning with Scikit-Learn to conduct text classification, such as automatically building machine learning systems that can determine positive versus negative movie reviews or spam versus legitimate email messages.
We will expand this knowledge to more complex unsupervised learning methods for natural language processing, such as topic modeling, where our machine learning models will detect topics and major concepts from raw text files.
This course even covers advanced topics, such as sentiment analysis of text with the NLTK\u00a0library, and creating semantic word vectors with the Word2Vec algorithm.
Included in this course is an entire section devoted to state-of-the-art advanced topics, such as using deep learning to build out our own chatbots!
Not only do you get fantastic technical content with this course, but you will also get access to both our course-related Question and Answer forums, as well as our live student chat channel, so you can team up with other students for projects, or get help on the course content from myself and the course teaching assistants.
All of this comes with a 30-day money-back guarantee, so you can try the course risk-free.
What are you waiting for? Become an expert in natural language processing today!
I will see you inside the course,
Jose
Goals
What will you learn in this course:
Learn to work with Text Files with Python
Learn how to work with PDF files in Python
Utilize Regular Expressions for pattern searching in text
Use Spacy for ultra fast tokenization
Learn about Stemming and Lemmatization
Understand Vocabulary Matching with Spacy
Use Part of Speech Tagging to automatically process raw text files
Understand Named Entity Recognition
Visualize POS and NER with Spacy
Use SciKit-Learn for Text Classification
Use Latent Dirichlet Allocation for Topic Modelling
Learn about Non-negative Matrix Factorization
Prerequisites
What are the prerequisites for this course?
Understand general Python
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
7 Lectures
- Promo 01:55 01:55
- Introduction to Course 00:55 00:55
- Introduction to Instructor 05:44 05:44
- Introduction to Co-Instructor 01:30 01:30
- Course Introduction 11:16 11:16
- Introduction To Instructor New 02:19 02:19
- Resources
Introduction(Regular Expressions)
4 Lectures
Meta Characters(Regular Expressions)
25 Lectures
Pattern Objects(Regular Expressions)
6 Lectures
More Meta Characters(Regular Expressions)
3 Lectures
String Modification(Regular Expressions)
4 Lectures
Words and Tokens(Text Preprocessing)
5 Lectures
Sentiment Classification(Text Preprocessing)
12 Lectures
Language Independent Tokenization(Text Preprocessing)
11 Lectures
Text Nomalization(Text Preprocessing)
4 Lectures
String Matching and Spelling Correction(Text Preprocessing)
8 Lectures
Language Modeling
10 Lectures
Topic Modelling with Word and Document Representations
16 Lectures
Word Embeddings LSI
12 Lectures
Word Semantics
13 Lectures
Word2vec(Optional)
13 Lectures
Need of Deep Learning for NLP(NLP with Deep Learning DNN)
3 Lectures
Introduction(NLP with Deep Learning DNN)
11 Lectures
Training(NLP with Deep Learning DNN)
9 Lectures
Hyper parameters(NLP with Deep Learning DNN)
10 Lectures
Introduction(NLP with Deep Learning RNN)
7 Lectures
Mini-project Language Modelling(NLP with Deep Learning RNN)
10 Lectures
Mini-project Sentiment Classification(NLP with Deep Learning RNN)
6 Lectures
RNN in PyTorch(NLP with Deep Learning RNN)
10 Lectures
Advanced RNN models(NLP with Deep Learning RNN)
2 Lectures
Neural Machine Translation
13 Lectures
Instructor Details
AISciences
We are a group of experts, PhDs, and Practitioners of Artificial Intelligence, Computer Science, Machine Learning, and Statistics. Some of us work in big companies like Amazon, Google, Facebook, Microsoft, KPMG, BCG, and IBM.
We decided to produce a series of courses mainly dedicated to beginners and newcomers on the techniques and methods of Machine Learning, Statistics, Artificial Intelligence, and Data Science.
Initially, our objective was to help only those who wish to understand these techniques more easily and to be able to start without too much theory and without a long reading. Today we also publish a more complete course on some topics for a wider audience.
Our courses have had phenomenal success. Our Courses have helped more than 100,000 students to master AI and Data Science.
✅ Stay Connected to Us.
👉 Twitter: https://twitter.com/AISciencesLearn
👉 Facebook: https://www.facebook.com/AISciencesLearn
👉 LinkedIn: https://www.linkedin.com/company/ai-sciences/
👉 Website: http://www.aisciences.io
✅ For Business Inquires: contact@aisciences.io
Course Certificate
User your certification to make a career change or to advance in your current career. Salaries are among the highest in the world.
Our students work
with the Best
Related Video Courses
View MoreAnnual Membership
Become a valued member of Tutorials Point and enjoy unlimited access to our vast library of top-rated Video Courses
Subscribe nowOnline Certifications
Master prominent technologies at full length and become a valued certified professional.
Explore Now