JOHN SIR

2.1 Syntax Parsing- Types of Grammars- CFG

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2.2 CFG parsing- Limitations

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2.3 Tree Banks- Types of tree banks

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1.1 Applications of NLP - Demo

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1.0 What is NLP

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Linear Regression in R

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Line plot & Scatter plot in R

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Histogram in R

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Box plot in R

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Pie Chart, Bar Chart in R

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Practical Methodology - Deep Learning

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Problems with RNN- Vanishing Gradient- Exploding Gradient Problems

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BPTT- Back Propagation Through Time - RNN- part-1

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BPTT- Back Propagation Through Time - RNN- part-2- Derivation

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OPERATORS -CONDITIONAL STATEMENTS

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Introduction to RNN

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CNN- Introduction

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Matrix, Array in R

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Matrix- in - R (creating matrix, using matrix( ), rbind( ), cbind( )

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Introduction to Convolution

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Vectors in R

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Data Types in R

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Introduction to R - Installation of R, R-Studio- Running R on Kaggle Notebook

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Central Tendency Measures & Dispersion of Data - Introduction to Data Science Unit-2

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Types of Attributes - Introduction to Data Science - Unit-2

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L2-Regularization(Ridge Regression) - Mathematical intuition- Weight Decay

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Regularization-Overfitting- Norms- Intro

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Solving XOR problem with hidden layer; Numerical Example

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Deep Learning Review of Machine Learning

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What is Data Science- Enormity of Data in 2025

JOHN SIR