NLP Foundations
Learn all the fundamental skills of Natural Language Processing (NLP) theory and practice. From tokenization to sentiment analysis, this course covers it all. Perfect for AI professionals, Python programmers, and machine learning students. Start your NLP journey today!
What you’ll learn
- Natural Language Processing theory and practice
- Main topics such as Tokenization, Stopwords, Stemming, Lemmatization, PoS, NER, BoW, TF-IDF and Embeddings including an hands-on part for each of them
- Coding Projects with Sentiment Analysis, Text Classification and Summarization
- AI Ethics Principles applied to NLP and NLU
Let’s understand NLP and get all fundamental skills from SCRATCH!
In this course you are invited to learn all the fundamental skills required in any kind of activity related to the Natural Language Processing and you will learn them from a theoretical and practical point of view, in fact you will seat together with me coding and implementing any topic step-by-step, instruction after instruction.
Moreover we are going to create from zero three extremely interesting projects:
Text Classification
Sentiment Analysis
Summarization
Any of these projects will be a real and working use case so you will be able to re-use them in your own apps.
In few words, this course is a real journey inside Natural Language Processing starting from the very beginning and finishing with the idea that all modern systems are leveraging: word embeddings.
We are exploring NLU, NLG, NLP History, applications and use cases, studing Tokenization, Stopwords, Stemming, Lemmatization, PoS, NER, BoW, TF-IDF and Embeddings.
Beside all this large content we are keeping an eye even on the AI Ethics because from very strong power always derives a strong responsibility too.
At the end of the videos and hands-on parts you will be ready to continue by yourself facing any kind of challenge in the fashinating NLP world!
Don’t hesitate to contact me for any kind of question!
CHEERS!
Who this course is for:
- AI Professionals, Python Programmers, Machine Learning Students, Computer Science Students, IT Passionates
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