Скачать или смотреть Classic Machine Learning Models for NLP

This video explores the foundational Classic Machine Learning Models that powered NLP before the era of deep learning and are still valued today for their simplicity, speed, and reliability.

The "Workhorses": The video introduces key algorithms that act as a "Swiss Army Knife" for text analysis:

Logistic Regression: The go-to for simple classification.

Naive Bayes: Excellent for probabilistic text analysis.

Support Vector Machines (SVM): Great at finding dividing lines between data types.

Decision Trees & K-Nearest Neighbors: Other essential tools for making choices and classifying based on proximity.

Real-World Impact: These models are described as "unsung heroes" running behind the scenes in everyday tools like spam filters, sentiment analysis on product reviews, and news categorization.

The Workflow: It breaks down the process: Pre-processing (cleaning text) - Vectorization (converting text to numbers using Bag of Words or TF-IDF) - Model Training - Prediction.

Feature Engineering: Emphasizes that feeding the model the right "ingredients" (features) is often more critical than the model choice itself.

#NLP #MachineLearning #DataScience #LogisticRegression #NaiveBayes #ArtificialIntelligence #TextAnalysis #Python #ScikitLearn #Algorithms