ENTIRE Natural Language Processing CRASH COURSE in 45 MINS!
Welcome to this 1-hour NLP Crash Course.
By the end of this video, you’ll go from "I've heard of NLP" to "I understand how it works and can build my first NLP models."
What you’ll learn in this crash course:
What is Natural Language Processing (NLP) and why it’s hard
Real-world applications: chatbots, Google Translate, sentiment analysis, and more
The NLP workflow: Data → Preprocessing → Feature Extraction → Model Training → Evaluation → Deployment
Core concepts: Tokenization, stopword removal, stemming, lemmatization, text representation
NLP tasks: Sentiment Analysis, Spam Detection, Translation, Summarization, Question Answering
Advanced topics: Transformers, Hugging Face, BERT, GPT, Retrieval-Augmented Generation, Prompt Engineering
The future of NLP: multimodal AI, multilinguality, personalization, and beyond
This crash course is designed for students, developers, and AI enthusiasts who want to quickly grasp the foundations of NLP and see practical examples with code.
Resources mentioned in this video:
Hugging Face Transformers: https://huggingface.co/transformers
Kaggle NLP Datasets: https://www.kaggle.com/datasets
If you found this helpful, don’t forget to Like, Share, and Subscribe to support the channel.
Turn on notifications so you never miss future crash courses on AI, ML, Cloud, and Computer Science.
#NLP #NaturalLanguageProcessing #NLPAlgorithms #NLPTasks #NLPTutorial #NLPModels #NLPCourse #NLPTraining #NLPProjects #NLPCommunity #AI #ArtificialIntelligence #MachineLearning #DeepLearning #DataScience
Welcome to this 1-hour NLP Crash Course.
By the end of this video, you’ll go from “I’ve heard of NLP” to “I understand how it works and can build my first NLP models.”
What you’ll learn in this crash course:
What is Natural Language Processing (NLP) and why it’s hard
Real-world applications: chatbots, Google Translate, sentiment analysis, and more
The NLP workflow: Data → Preprocessing → Feature Extraction → Model Training → Evaluation → Deployment
Core concepts: Tokenization, stopword removal, stemming, lemmatization, text representation
NLP tasks: Sentiment Analysis, Spam Detection, Translation, Summarization, Question Answering
Advanced topics: Transformers, Hugging Face, BERT, GPT, Retrieval-Augmented Generation, Prompt Engineering
The future of NLP: multimodal AI, multilinguality, personalization, and beyond
This crash course is designed for students, developers, and AI enthusiasts who want to quickly grasp the foundations of NLP and see practical examples with code.
Resources mentioned in this video:
Hugging Face Transformers: https://huggingface.co/transformers
Kaggle NLP Datasets: https://www.kaggle.com/datasets
If you found this helpful, don’t forget to Like, Share, and Subscribe to support the channel.
Turn on notifications so you never miss future crash courses on AI, ML, Cloud, and Computer Science.
#NLP #NaturalLanguageProcessing #NLPAlgorithms #NLPTasks #NLPTutorial #NLPModels #NLPCourse #NLPTraining #NLPProjects #NLPCommunity #AI #ArtificialIntelligence #MachineLearning #DeepLearning #DataScience
