- Section Introduction Pro
- NLP Pipeline Pro
- Text Preprocessing Overview Pro
- ASSIGNMENT: Create a New Environment Pro
- SOLUTION: Create a New Environment Pro
- Text Preprocessing with Pandas Pro
- DEMO: Text Preprocessing Setup Pro
- DEMO: Text Preprocessing with Pandas Pro
- PRO TIP: Create a Function Pro
- ASSIGNMENT: Text Preprocessing with Pandas Pro
- SOLUTION: Text Preprocessing with Pandas Pro
- Text Preprocessing with spaCy Pro
- Tokenization Pro
- Lemmatization Pro
- Stop Words Pro
- Parts of Speech Tagging Pro
- DEMO: Tokens, Lemmas & Stop Words Pro
- PRO TIP: Use the Apply Method Pro
- DEMO: Parts of Speech Tagging Pro
- DEMO: Create an NLP Pipeline Pro
- ASSIGNMENT: Text Preprocessing with spaCy Pro
- SOLUTION: Text Preprocessing with spaCy Pro
- Vectorization Pro
- Count Vectorizer in Python Pro
- DEMO: Count Vectorizer Pro
- DEMO: Count Vectorizer Parameters Pro
- PRO TIP: Exploratory Data Analysis Pro
- ASSIGNMENT: Count Vectorizer Pro
- SOLUTION: Count Vectorizer Pro
- TF-IDF Pro
- TF-IDF Vectorizer in Python Pro
- DEMO: TF-IDF Vectorizer Pro
- ASSIGNMENT: TF-IDF Vectorizer Pro
- SOLUTION: TF-IDF Vectorizer Pro
- Key Takeaways Pro
- Section Introduction Pro
- What is Machine Learning? Pro
- Common ML Algorithms for NLP Pro
- Traditional NLP Overview Pro
- Traditional vs Modern NLP Pro
- DEMO: Create a New Environment Pro
- Sentiment Analysis Pro
- Sentiment Analysis in Python Pro
- DEMO: Sentiment Analysis in Python Pro
- ASSIGNMENT: Sentiment Analysis Pro
- SOLUTION: Sentiment Analysis Pro
- Text Classification Basics Pro
- Text Classification Algorithms Pro
- Naïve Bayes Pro
- Naïve Bayes in Python Pro
- DEMO: Naïve Bayes Setup Pro
- DEMO: Naïve Bayes Workflow Pro
- DEMO: Naïve Bayes Prediction Pro
- PRO TIP: Compare ML Models Pro
- Text Classification Next Steps Pro
- ASSIGNMENT: Text Classification Pro
- SOLUTION: Text Classification Pro
- Topic Modeling Basics Pro
- Topic Modeling Algorithms Pro
- Non-Negative Matrix Factorization (NMF) Pro
- NMF in Python Pro
- DEMO: Fit an NMF Model Pro
- PRO TIP: Display Topics Function Pro
- DEMO: Tune an NMF Model Pro
- Topic Modeling Next Steps Pro
- PRO TIP: Combine ML Algorithms Pro
- ASSIGNMENT: Topic Modeling Pro
- SOLUTION: Topic Modeling Pro
- Key Takeaways Pro
- Section Introduction Pro
- Modern NLP Overview Pro
- Intro to Neural Networks Pro
- Logistic Regression Refresher Pro
- Logistic Regression: Visually Explained Pro
- Neural Networks: Visually Explained Pro
- Neural Network Summary Pro
- EXERCISE: Neural Network Components Pro
- SOLUTION: Neural Network Components Pro
- Neural Networks in Python Pro
- DEMO: Neural Networks in Python Pro
- DEMO: Neural Network Matrices Pro
- PRO TIP: NN Notation & Matrices Pro
- How a Neural Network is Trained Pro
- Neural Network Training: Visually Explained Pro
- EXERCISE: Neural Network Training Pro
- SOLUTION: Neural Network Training Pro
- Intro to Deep Learning Pro
- Deep Learning Architectures Pro
- Deep Learning in Practice Pro
- Pretrained Deep Learning Models Pro
- EXERCISE: Deep Learning Concepts Pro
- SOLUTION: Deep Learning Concepts Pro
- Key Takeaways Pro
- Section Introduction Pro
- Modern NLP Recap Pro
- Transformers & LLMs Overview Pro
- Transformer Architecture Pro
- Transformer Architecture | Embeddings Pro
- Transformer Architecture | Attention Pro
- Transformer Architecture | Feedforward Neural Network Pro
- Transformers Summary Pro
- Breaking Down the Transformer Diagram Pro
- Encoders & Decoders Pro
- Large Language Models (LLMs) Pro
- EXERCISE: Transformers & LLMs Concepts Pro
- SOLUTION: Transformers & LLMs Concepts Pro
- Key Takeaways Pro
- Section Introduction Pro
- Hugging Face Overview Pro
- DEMO: Create a New Environment Pro
- Sentiment Analysis with LLMs Pro
- DEMO: Basic Sentiment Analysis Pipeline Pro
- DEMO: Timing, Logging and Device Setup Pro
- DEMO: Compare Sentiment Scores Pro
- PRO TIP: Speed Up Transformers Code Pro
- ASSIGNMENT: Sentiment Analysis with LLMs Pro
- SOLUTION: Sentiment Analysis with LLMs Pro
- Named Entity Recognition Pro
- DEMO: Basic NER Pipeline Pro
- DEMO: Hugging Face Model Hub Pro
- DEMO: Clean NER Output Pro
- ASSIGNMENT: Named Entity Recognition Pro
- SOLUTION: Named Entity Recognition Pro
- Zero-Shot Classification Pro
- DEMO: Zero-Shot Classification Pro
- ASSIGNMENT: Zero-Shot Classification Pro
- SOLUTION: Zero-Shot Classification Pro
- Text Summarization Pro
- DEMO: Text Summarization Pro
- DEMO: Multiple Pipelines Pro
- ASSIGNMENT: Text Summarization Pro
- SOLUTION: Text Summarization Pro
- PRO TIP: Text Generation Pro
- Document Embeddings Pro
- Cosine Similarity Pro
- Document Similarity with Embeddings Pro
- DEMO: Feature Extraction & Embeddings Pro
- DEMO: Cosine & Document Similarity Pro
- PRO TIP: Recommender Function Pro
- ASSIGNMENT: Document Similarity Pro
- SOLUTION: Document Similarity Pro
- Key Takeaways Pro