Published 10/2024
Created by Zeeshan Ahmad
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 195 Lectures ( 27h 6m ) | Size: 9.2 GB
NLP : NLTK, Machine and Deep Learning for NLP, Word Embeddings, Markov Model, Transformers, Generative AI for text
What you’ll learn
Text Preprocessing and Text Vectorization
Machine Learning Methods for Text Classification
Neural Networks for Text Classification
Sentiment Analysis and Spam Detection
Topic Modeling
Word Embeddings and Neural Word Embeddings
Word2Vec and GloVe
Generative AI for Text data
Markov Models for Text Generation
Recurrent Neural Networks and LSTM
Seq2Seq Networks for Text Generation
Machine Translation
Transformers
Requirements
Some Python Programming Knowledge
Some knowledge about machine learning is preferred
Description
Hi everyone,This is a massive 3-in-1 course covering the following:1. Text Preprocessing and Text Vectorization2. Machine Learning and Statistical Methods3. Deep Learning for NLP and Generative AI for text.This course covers all the aspects of performing different Natural Language processing using Machine Learning Models, Statistical Models and State of the art Deep Learning Models such as LSTM and Transformers.This course will set the foundation for learning the most recent and groundbreaking topics in AI related Natural processing tasks such as Large Language Models, Diffusion models etc.This course includes the practical oriented explanations for all Natural Language Processing tasks with implementation in PythonSections of the Course· Introduction of the Course· Introduction to Google Colab· Introduction to Natural Language Processing· Text Preprocessing· Text Vectorization· Text Classification with Machine Learning Models· Sentiment Analysis· Spam Detection· Dirichlet Distribution· Topic Modeling· Neural Networks· Neural Networks for Text Classification· Word Embeddings· Neural Word Embeddings· Generative AI for NLP· Markov Model for Text Generation· Recurrent Neural Networks ( RNN )· Sequence to sequence Networks· Transformers· Bidirectional LSTM· Python RefresherWho this course is for:· Students enrolled in Natural Language processing course.· Beginners who want to learn Natural Language Processing from fundamentals to advanced level· Researchers in Artificial Intelligence and Natural Language Processing.· Students and Researchers who want to develop Python Programming skills while solving different NLP tasks.· Want to switch from Matlab and Other Programming Languages to Python.
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