Natural Language Processing
Natural Language Processing (NLP) - from Tokenization, Embeddings, Transformers to LLMs
Courses
AI & ML Courses Overview
less than a minute
This course includes
133 articles
8h 3m reading time
198 videos • 71 hr 10 mins
Course content
4 sections • 882 topics • Read: 8h 3m • Video: 71 hr 10 mins
Natural Language Processing
Introduction
Text Pre-Processing
Tokenization
Text Embedding
RNN
LSTM
GRU
Attention
Self Attention
Transformer
LLM
BERT
Deep Learning
Introduction
XOR Problem
Activation Function
Optimization Method
Regularization
Batch Normalization
Back Propagation
Machine Learning
Introduction
Supervised Learning
Unsupervised Learning
Feature Engineering
ML System
Interview Questions
Maths
Probability
Statistics
Linear Algebra
Calculus
Deep Learning
Deep Learning - from Neural Networks, Activation Functions, to Back Propagation
Machine Learning
Classical ML - Supervised & Unsupervised Learning, Feature Engineering, & ML Systems
Maths
Mathematics for AI & ML - Probability, Statistics, Linear Algebra, & Calculus