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Lecture 14 of 29

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Section 1: BERT - Intuition8 videos

What is BERT

9m

General Idea

14m

Embedding

25m

Old fashioned seq2seq

10m

Transformer general understanding

12m

Attention

30m

Pre-training

12m

Architecture

35m
Section 2: Introduction1 videos

Welcome to the course

16m
Section 3: Application using BERT's tokenizer10 videos

CNN explanation

18m

Intro

7m

Loading Files

9m

Cleaning Data

13m

Dependencies

23mNow Playing

Tokenization

11m

Training

22m

Model Building

18m

Evaluation

10m

Dataset Creation

39m
Section 4: Application using BERT as an embedder2 videos

Inputs

18m

Model Results

19m
Section 5: Application fine-tuning BERT to create a question answering system8 videos

Intro

15m

Data Preprocessing

9m

Squad Layer

10m

Evaluation Preparation

6m

Evaluation Result

2m

Whole Model

9m

Compile AI

13m

Evaluation Creation

15m