Generative AI – Natural Language Processing Bootcamp 2024
Generative AI – Natural Language Processing Bootcamp 2024, available at $79.99, has an average rating of 4.41, with 117 lectures, 3 quizzes, based on 260 reviews, and has 1952 subscribers.
You will learn about Text Preprocessing using NLTK and Spacy How to work on NLP pipeline Perform Tokenization Stemming & Lemmatization Apply Word Embeddings NLP Pipeline for various tasks Named Entity Recognition Text Summarization Building an Enterprise Grade Chatbot with Dialogflow Building a project on Twitter Tweets Build Chatbot with RASA with Advanced Integration Deep Learning for Sequence Data Transformer NLP Architecture ChatGPT BERT Model Hugging Face Transformers This course is ideal for individuals who are Anyone who wants to learn natural language processing (NLP) or Anyone interested in artificial intelligence, machine learning, deep learning, or data science or Anyone who wants to build Advanced NLP models and implement in a project or Anyone who wants to create Enterprise Grade Chatbots It is particularly useful for Anyone who wants to learn natural language processing (NLP) or Anyone interested in artificial intelligence, machine learning, deep learning, or data science or Anyone who wants to build Advanced NLP models and implement in a project or Anyone who wants to create Enterprise Grade Chatbots.
Enroll now: Generative AI – Natural Language Processing Bootcamp 2024
Summary
Title: Generative AI – Natural Language Processing Bootcamp 2024
Price: $79.99
Average Rating: 4.41
Number of Lectures: 117
Number of Quizzes: 3
Number of Published Lectures: 117
Number of Published Quizzes: 3
Number of Curriculum Items: 120
Number of Published Curriculum Objects: 120
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- Text Preprocessing using NLTK and Spacy
- How to work on NLP pipeline
- Perform Tokenization
- Stemming & Lemmatization
- Apply Word Embeddings
- NLP Pipeline for various tasks
- Named Entity Recognition
- Text Summarization
- Building an Enterprise Grade Chatbot with Dialogflow
- Building a project on Twitter Tweets
- Build Chatbot with RASA with Advanced Integration
- Deep Learning for Sequence Data
- Transformer NLP Architecture
- ChatGPT
- BERT Model
- Hugging Face Transformers
Who Should Attend
- Anyone who wants to learn natural language processing (NLP)
- Anyone interested in artificial intelligence, machine learning, deep learning, or data science
- Anyone who wants to build Advanced NLP models and implement in a project
- Anyone who wants to create Enterprise Grade Chatbots
Target Audiences
- Anyone who wants to learn natural language processing (NLP)
- Anyone interested in artificial intelligence, machine learning, deep learning, or data science
- Anyone who wants to build Advanced NLP models and implement in a project
- Anyone who wants to create Enterprise Grade Chatbots
Embark on an Exhilarating NLP Journey: From Zero to Hero in Practical Natural Language Processing
Unleash the immense potential of Natural Language Processing (NLP) with our comprehensive course, meticulously crafted to transform you from a novice to a master in text processing, chatbot development, and cutting-edge techniques like BERT and Transformer NLP Architecture.
Why Choose This Course?
1. Empowering Your NLP Mastery:
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Navigate the intricate world of NLP, understanding its profound impact on human communication.
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Harness NLP’s potential to build applications for seamless human interaction, enhanced efficiency, and automation of tedious tasks.
2. Accelerating Career Opportunities:
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Elevate your career in software development, data science, and marketing by mastering the interdisciplinary and rapidly growing field of NLP.
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Open doors to diverse industries seeking NLP expertise, from software development to marketing.
3. Benefits of NLP Learning:
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Gain a profound understanding of human communication dynamics through NLP.
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Develop applications that enhance human interaction and task automation.
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Automate tedious tasks such as information extraction from unstructured text data.
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Improve the usability of search engines and information retrieval systems.
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Unlock career opportunities in software development, data science, marketing, and more.
4. A Unique Learning Experience:
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Explore a meticulously designed curriculum that caters to practitioners seeking in-depth knowledge of NLP.
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Progress through essential topics, building a solid foundation for advanced techniques.
5. Key Topics Covered:
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Text Processing Fundamentals:
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Dive into crucial aspects such as text preprocessing, NLP pipeline, tokenization, stemming, lemmatization, word embeddings, and NLP pipeline for various tasks.
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Enterprise-Grade Chatbot Development with DialogFlow:
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Build a robust chatbot using Google Cloud Platform’s service – DialogFlow.
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Leverage advanced machine learning models seamlessly with a few clicks for immediate implementation.
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Twitter Project – Real-time Data Extraction and Analysis:
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Engage in an end-to-end project using the Tweepy library to extract, mine, preprocess text data from Twitter.
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Create real-time word clouds based on live tweets, providing practical, hands-on experience.
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RASA Chatbot with Advanced Integration:
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Explore Rasa, an open-source chatbot framework, for building contextual assistants.
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Implement Rasa from scratch, integrating it with Slack channels and enabling functionalities such as retrieving news from the New York Times website.
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Deep Learning for Sequence Data:
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Move beyond traditional machine learning, delving into deep learning neural networks.
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Explore the latest advancements in NLP research, including recurrent neural networks, LSTM neural networks, and attention mechanisms for encoder-decoder architecture.
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Transformer NLP Architecture:
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Witness the transformative impact of transformer NLP architecture on solving natural language tasks.
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Understand how businesses leverage this technology for extracting meaningful insights from large volumes of text data.
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Revolutionary ChatGPT Technology:
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Grasp the essence of ChatGPT, a revolutionary AI technology automating mundane business tasks.
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Learn the intuition behind ChatGPT and its applications in customer support, onboarding, training, sales, and marketing.
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BERT Model – Unveiling Core Architectures:
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Explore BERT (Bidirectional Encoder Representations from Transformers), a groundbreaking AI designed for profound understanding of natural language.
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Delve into sentiment analysis, question-answering, and text summarization using the core architecture of BERT.
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Hugging Face Transformers:
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Navigate the realm of Hugging Face transformers, a platform offering access to state-of-the-art pre-trained models.
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Implement these models hands-on, gaining insights into the latest advancements in NLP.
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6. Seize the Learning Advantage:
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Benefit from a practitioner-led course that ensures hands-on learning and practical insights.
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Stay ahead in the ever-evolving NLP landscape with a comprehensive curriculum designed for seamless progression.
7. Take the Leap into a Transformative NLP Future:
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Experience the thrill of going from zero to hero in Practical Natural Language Processing.
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Invest in your future with a course that not only imparts knowledge but also cultivates practical skills.
Don’t miss this chance to elevate your proficiency in NLP. Click the “Enroll Now” button and be part of a transformative learning journey. Every second counts, and the opportunity to become an NLP hero awaits.
Course Curriculum
Chapter 1: Introduction to Natural Language Processing
Lecture 1: Why NLP and how its different from Normal ML ?
Lecture 2: Understanding Human Language
Lecture 3: Challenges of NLP
Lecture 4: Summary
Lecture 5: Source code link for the course
Lecture 6: Connect with Instructor
Chapter 2: Pipeline of NLP
Lecture 1: Attachments of this section – Code Reference
Lecture 2: NLP Pipeline
Lecture 3: Data Extraction and Text Cleaning hands On
Lecture 4: Introduction to NLTK library
Lecture 5: Tokenization , bigrams, trigrams, and N gram – Hands on
Lecture 6: POS Tagging & Stop Words Removal
Lecture 7: Stemming & Lemmatization
Lecture 8: NER and Wordsense Disambiguation
Lecture 9: Introduction to Spacy Library
Lecture 10: Hands On Spacy
Lecture 11: Summary
Chapter 3: NLP -Text Vectorization
Lecture 1: Attachments of this section – Code Reference
Lecture 2: Vector Representation of Text – One Hot Encoding
Lecture 3: Understanding BoW Technique
Lecture 4: BoW Hands On
Lecture 5: TF-IDF
Lecture 6: TF-IDF Hands On
Lecture 7: Tf-idf from Scratch Implementation
Chapter 4: Word Embeddings
Lecture 1: Attachments of this section – code reference
Lecture 2: Introduction to Word Embeddings
Lecture 3: Intuition of Vector Representation
Lecture 4: Hands On Word Embeddings – Usage of Pre-trained models
Lecture 5: Skip-gram Word Embeddings – Understanding Data Preperation
Lecture 6: Skip Gram Model Architecture
Lecture 7: Skip Gram Hands On – Deep Dive
Lecture 8: CBOW Model Architecture & Hands On
Lecture 9: Hyperparameters – Negative Sampling and Sub Sampling
Lecture 10: Practical Difference between CBOW and Skip-gram
Lecture 11: Bonus : How does a Network is trained – Back-propagation
Lecture 12: Section Summary
Chapter 5: End to End Pipeline for Text Classification
Lecture 1: Code Attachments for this section
Lecture 2: General Pipeline for Classification
Lecture 3: Approaches to Classification
Lecture 4: Loading the Dataset
Lecture 5: Exploratory Data Analysis & Text Preprocessing
Lecture 6: Remove Low Frequency Words
Lecture 7: Remove Stop Words with Stemming & Lemmatisation
Lecture 8: Application of Model
Lecture 9: TfIDF Approach
Lecture 10: Challenges of NLP & N-grams
Chapter 6: Information Extraction
Lecture 1: Introduction to NER
Lecture 2: Understanding CRF – Introduction
Chapter 7: Chatbots – Build with Google Cloud Service – Dialogflow
Lecture 1: Attachments for the section – Code Reference
Lecture 2: Understanding Chatbots
Lecture 3: Building a Simple Chatbot
Lecture 4: Hands On Building a Simple FAQ Chatbot
Lecture 5: Types of Chatbot and Pipeline for Chatbot
Lecture 6: Terminologies in Chatbot
Lecture 7: Dialog flow – Introduction
Lecture 8: Basics of Dialogflow
Lecture 9: Dialogflow system setup
Lecture 10: Create Dialogflow chatbot
Lecture 11: Dialogflow Fulfilment
Lecture 12: Dialogflow Integrations/Deployment
Lecture 13: Dialogflow Miscellaneous Tools
Chapter 8: Deep Dive into the Dialog Systems (Chatbot)
Lecture 1: Attachments for the section – code reference
Lecture 2: Deep Dive into the components of Dialog System
Lecture 3: Dialog Intent Prediction
Lecture 4: Deep Learning based intent Classification
Chapter 9: Project – Build Chatbot using RASA
Lecture 1: Project Files for RASA
Lecture 2: Introduction to RASA Chatbot
Lecture 3: Installation of RASA
Lecture 4: RASA project Structure
Lecture 5: RASA Files
Lecture 6: Basics of YAML
Lecture 7: Building the chatbot – Add intents and Response
Lecture 8: Building the chatbot – Extract Entity & working with Slots
Lecture 9: Create API Key from NyTimes
Lecture 10: Working with Action File – Demo
Lecture 11: Building Custom Action File
Lecture 12: Test the Action Server
Lecture 13: RASA Pipeline file
Lecture 14: RASA Deployment – Integration with RASA Chatbot – Pre-requisites
Lecture 15: Run Ngork on RASA Chatbot with Actions
Lecture 16: Slack Settings for Connection to RASA Chatbot
Lecture 17: Practice Project Concert Chatbot & Summary
Chapter 10: Text Summarization
Lecture 1: Code File for Reference
Lecture 2: Text Summarization – Introduction
Lecture 3: Hands On Text Summarization
Chapter 11: NLP Project – Analyze Tweets from Twitter
Lecture 1: Code Reference file for the Section
Instructors
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Manifold AI Learning ®
Learn the Future – Data Science, Machine Learning & AI
Rating Distribution
- 1 stars: 6 votes
- 2 stars: 7 votes
- 3 stars: 22 votes
- 4 stars: 81 votes
- 5 stars: 144 votes
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