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Natural Language Processing (NLP) at UT Austin Full Course – Classification, Sentiment Analysis & ML
Multiclass Perceptron and Logistic Regression

Multiclass Perceptron and Logistic Regression

Natural Language Processing (NLP) at UT Austin Full Course – Classification, Sentiment Analysis & ML

محتوى الكورس

جميع الدروس
98 درس
05:50 Instruction Tuning (Natural Language Processing at UT Austin)
05:52 BERT For QA (Natural Language Processing at UT Austin)
09:54 Reading Comprehension: Setup And Baselines (Natural Language Processing at UT Austin)
08:57 Reading Comprehension Intro (Natural Language Processing at UT Austin)
05:54 Chain of Thought: Extensions and Analysis (Natural Language Processing at UT Austin)
07:01 Chain of Thought (Natural Language Processing at UT Austin)
13:01 Text Explanations (Natural Language Processing at UT Austin)
10:06 Annotation Artifacts (Natural Language Processing at UT Austin)
08:05 Model Probing (Natural Language Processing at UT Austin)
14:22 Local Explanations: Highlights (Natural Language Processing at UT Austin)
08:20 Explainability In NLP (Natural Language Processing at UT Austin)
09:56 Factuality of LLMs (Natural Language Processing at UT Austin)
08:13 Reinforcement Learning from Human Feedback (Natural Language Processing at UT Austin)
08:08 Problems With Reading Comprehension (Natural Language Processing at UT Austin)
07:29 Understanding ICL: Induction Heads (Natural Language Processing at UT Austin)
08:18 Few-shot Prompting (Natural Language Processing at UT Austin)
08:28 Zero-shot Prompting (Natural Language Processing at UT Austin)
09:29 GPT-3 (Natural Language Processing at UT Austin)
16:00 Transition Based Dependency Parsing (Natural Language Processing at UT Austin)
14:37 Dependencies (Natural Language Processing at UT Austin)
11:31 Refining Grammars (Natural Language Processing at UT Austin)
14:29 CKY Algorithm (Natural Language Processing at UT Austin)
13:33 Probabilistic Context Free Grammars (Natural Language Processing at UT Austin)
15:07 Constituency Parsing (Natural Language Processing at UT Austin)
13:49 HMMs for POS Tagging (Natural Language Processing at UT Austin)
06:30 Summarization Intro (Natural Language Processing at UT Austin)
09:03 Ethics: Unethical Use (Natural Language Processing at UT Austin)
06:59 Ethics: Dangers of Automation (Natural Language Processing at UT Austin)
05:50 Ethics: Exclusion (Natural Language Processing at UT Austin)
06:25 Ethics: Bias (Natural Language Processing at UT Austin)
08:09 Language and Vision (Natural Language Processing at UT Austin)
09:38 Language Grounding (Natural Language Processing at UT Austin)
10:51 Cross-Lingual Pre-training (Natural Language Processing at UT Austin)
07:34 Cross Lingual Tagging And Parsing (Natural Language Processing at UT Austin)
09:33 Morphology (Natural Language Processing at UT Austin)
06:55 Pre-trained Summarization and Factuality (Natural Language Processing at UT Austin)
15:17 Extractive Summarization (Natural Language Processing at UT Austin)
20:06 HMMs: Viterbi Algorithm (Natural Language Processing at UT Austin)
07:52 Neural and Pretrained Machine Translation (Natural Language Processing at UT Austin)
14:57 Phrase Based Machine Translation (Natural Language Processing at UT Austin)
20:20 MT: IBM Models (Natural Language Processing at UT Austin)
06:42 MT: Word Alignment (Natural Language Processing at UT Austin)
12:53 MT: Framework, Evaluation (Natural Language Processing at UT Austin)
07:39 Machine Translation Intro (Natural Language Processing at UT Austin)
10:10 Neural Chatbots (Natural Language Processing at UT Austin)
11:07 Task-Oriented Dialogue (Natural Language Processing at UT Austin)
10:00 Dialogue: Chatbots (Natural Language Processing at UT Austin)
09:00 Multi-hop QA (Natural Language Processing at UT Austin)
06:59 Open-Domain QA (Natural Language Processing at UT Austin)
09:05 Multiclass Classification Examples (Natural Language Processing at UT Austin)
11:16 n-gram LMs (Natural Language Processing at UT Austin)
08:57 Applying Embeddings, Deep Averaging Networks (Natural Language Processing at UT Austin)
05:43 Bias In Word Embeddings (Natural Language Processing at UT Austin)
19:16 Other Word Embedding Methods (Natural Language Processing at UT Austin)
16:52 Skip-gram (Natural Language Processing at UT Austin)
13:27 Word Embeddings (Natural Language Processing at UT Austin)
15:25 Neural Net Training, Optimization (Natural Language Processing at UT Austin)
14:30 Neural Net Implementation (Natural Language Processing at UT Austin)
13:15 Feedforward Neural Networks, Backpropagation (Natural Language Processing at UT Austin)
05:11 Neural Network Visualization (Natural Language Processing at UT Austin)
13:33 Neural Networks (Natural Language Processing at UT Austin)
09:45 Fairness in Classification (Natural Language Processing at UT Austin)
10:33 Smoothing In n-gram LMs (Natural Language Processing at UT Austin)
17:10 Multiclass Perceptron and Logistic Regression
14:22 Multiclass Classification (Natural Language Processing at UT Austin)
15:09 Optimization Basics (Natural Language Processing at UT Austin)
06:30 Sentiment Analysis (Natural Language Processing at UT Austin)
20:58 Logistic Regression (Natural Language Processing at UT Austin)
12:53 Perceptron as Minimizing Loss (Natural Language Processing at UT Austin)
15:24 Perceptron (Natural Language Processing at UT Austin)
08:01 Basics of Learning, Gradient Descent (Natural Language Processing at UT Austin)
18:12 Sentiment Analysis and Basic Feature Extraction (Natural Language Processing at UT Austin)
06:29 Linear Binary Classification (Natural Language Processing at UT Austin)
21:28 Introduction (Natural Language Processing at UT Austin)
09:02 Beam Search (Natural Language Processing at UT Austin)
15:39 HMMs: Parameter Estimation (Natural Language Processing at UT Austin)
10:46 Hidden Markov Models (Natural Language Processing at UT Austin)
15:47 Sequence Labeling (Natural Language Processing at UT Austin)
17:00 Part-of-Speech Tagging (Natural Language Processing at UT Austin)
07:23 Word Piece And Byte Pair Encoding (Natural Language Processing at UT Austin)
05:07 T5 (Natural Language Processing at UT Austin)
05:40 BART (Natural Language Processing at UT Austin)
07:00 Seq2seq Models (Natural Language Processing at UT Austin)
14:43 BERT: Model and Applications (Natural Language Processing at UT Austin)
07:45 BERT: Masked Language Modeling (Natural Language Processing at UT Austin)
06:44 Nucleus Sampling (Natural Language Processing at UT Austin)
03:49 Course Preview (Natural Language Processing at UT Austin)
06:45 Transformer Extensions (Natural Language Processing at UT Austin)
10:28 Transformer Language Modeling (Natural Language Processing at UT Austin)
05:34 Using Transformers (Natural Language Processing at UT Austin)
07:46 Transformer Architecture (Natural Language Processing at UT Austin)
08:05 Position Encodings (Natural Language Processing at UT Austin)
05:27 Multi Head Self Attention (Natural Language Processing at UT Austin)
13:59 Self Attention (Natural Language Processing at UT Austin)
11:04 Attention (Natural Language Processing at UT Austin)
07:10 RNNs and their Shortcomings (Natural Language Processing at UT Austin)
07:17 Neural Language Models (Natural Language Processing at UT Austin)
03:09 LM Evaluation (Natural Language Processing at UT Austin)