TF-IDF Courses and Certifications

Introduction to TF-IDF Vectorization in Python

1 rating

Learn to convert text into TF-IDF numerical features in Python, customize vectorization parameters, remove stop words, and inspect influential terms for predictive modeling.

• CodeSignal
• 2 hours
• Self-Paced
• Free Certificate

James Briggs

Vector-Based Methods for Similarity Search - TF-IDF, BM25, SBERT

Compare TF-IDF, BM25, and Sentence-BERT for vector similarity and semantic search.

• YouTube
• 29 minutes
• Self-Paced
• Free Video

Feature Engineering for NLP in Python

151 ratings at DataCamp

In this course, you will learn techniques that will allow you to extract useful information from text and process them into a format suitable for applying ML models.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Combining the Best of Two Worlds: From TF-IDF to Llama LLM

Explore combining traditional NLP with LLMs to solve hallucination issues and create robust applications. Learn practical insights for leveraging foundational NLP principles alongside advanced LLM technology.

• YouTube
• 39 minutes
• Self-Paced
• Free Video

Foundations of NLP Data Processing

Build NLP preprocessing foundations through text cleaning, classical vectorization, tokenization, and word embeddings.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

Career Certificate

Introduction to Natural Language Processing

1 rating

Learn to explore and preprocess text, apply TF-IDF vectorization, and build and evaluate machine-learning classifiers in Python.

• CodeSignal
• 10 hours
• Self-Paced
• Free Certificate
• 4 courses

Feature Engineering for Text Classification

1 rating

Turn raw text into model-ready features: tokenize movie reviews, build Bag-of-Words and TF-IDF vectors, work with sparse matrices, and reduce dimensions with TruncatedSVD.

• CodeSignal
• 5 hours
• Self-Paced
• Free Certificate

Introduction to Recommender Systems: Non-Personalized and Content-Based

661 ratings at Coursera

Compute non-personalized, product-association, demographic, and content-based recommendations from datasets in spreadsheets, with an honors track implementing them in the open source LensKit toolkit.

• Coursera
• 6 weeks, 4 hours a week
• Self-Paced
• Paid Course

EDUCBA

Project on Recommendation Engine - Book Recommender

16 ratings at Coursera

Build a book recommendation engine in Python: preprocess data, engineer metadata filters, and apply TF-IDF, Count Vectorizers, and similarity matrices for content-based recommendations.

• Coursera
• 2 weeks, 3 hours a week
• Self-Paced
• Paid Course

Packt

NLP – Embeddings & Text Preprocessing in Python

Transform raw text into machine-learning-ready vectors: apply Bag of Words, Count Vectorizer, TF-IDF, tokenization, stemming, lemmatization, and neural word embeddings in Python.

• Coursera
• 7 weeks, 1 hour a week
• Self-Paced
• Paid Course

Build foundational NLP language models in Python, from bag-of-words and TF-IDF to word embeddings, through practical projects with text data.

• Codecademy
• 4 hours
• Self-Paced
• Free Trial Available

Introduction to Natural Language Processing

Build a practical foundation in natural language processing using Python. Learn to explore, preprocess, vectorize, and classify text data with common machine learning techniques.

• edX
• 3 weeks, 2-4 hours a week
• Self-Paced
• Free Online Course (Audit)

Python Tutorials for Digital Humanities

Topic Modeling and Text Classification with Python for Digital Humanities

Discover topic modeling and text classification techniques using Python libraries like Scikit-Learn, Gensim, and spaCy for digital humanities research and analysis.

• YouTube
• 3 hours 58 minutes
• Self-Paced
• Free Video

James Briggs

Vector Similarity Search and Faiss Course

Master vector similarity search techniques and Faiss implementation through hands-on practice with traditional methods, advanced indexing, and performance optimization strategies.

• YouTube
• 6 hours 16 minutes
• Self-Paced
• Free Video

Creating a Wordcloud using NLP and TF-IDF in Python

10 ratings at Coursera

Build a wordcloud from a Christmas recipes JSON dataset in Python: clean encodings, lemmatize text, compute TF-IDF weights, and package it as a reusable Jupyter notebook.

• Coursera
• 2 hours
• No Longer Offered
• Paid Course