NLP-Natural Language Processing in Python(Theory & Projects)

سرفصل های دوره

Mastering Natural Language Processing with Spacy, NLTK, PyTorch, NLP Techniques, Text Data Analysis, Hands-on Projects

1 - Introduction

1 - Introduction to Course

2 - Introduction to Instructor

3 - Introduction to CoInstructor

4 - Course Introduction

5 - Request for Your Honest Review

6 - Links for the Courses Materials and Codes.html

2 - IntroductionRegular Expressions

7 - Links for the Courses Materials and Codes.html

8 - What Is Regular Expression

9 - Why Regular Expression

10 - ELIZA Chatbot

11 - Python Regular Expression Package

3 - Meta CharactersRegular Expressions

12 - Links for the Courses Materials and Codes.html

13 - Meta Characters

14 - Meta Characters Bigbrackets Exercise

15 - Meta Characters Bigbrackets Exercise Solution

16 - Meta Characters Bigbrackets Exercise 2

17 - Meta Characters Bigbrackets Exercise 2 Solution

18 - Meta Characters Cap

19 - Meta Characters Cap Exercise 3

20 - Meta Characters Cap Exercise 3 Solution

21 - Backslash

22 - Backslash Continued

23 - Backslash Continued 01

24 - Backslash Squared Brackets Exercise

25 - Backslash Squared Brackets Exercise Solution

26 - Backslash Squared Brackets Exercise Another Solution

27 - Backslash Exercise

28 - Backslash Exercise Solution And Special Sequences Exercise

29 - Solution And Special Sequences Exercise Solution

30 - Meta Character Asterisk

31 - Meta Character Asterisk Exercise

32 - Meta Character Asterisk Exercise Solution

33 - Meta Character Asterisk Homework

34 - Meta Character Asterisk Greedymatching

35 - Meta Character Plus And Questionmark

36 - Meta Character Curly Brackets Exercise

37 - Meta Character Curly Brackets Exercise Solution

4 - Pattern ObjectsRegular Expressions

38 - Links for the Courses Materials and Codes.html

39 - Pattern Objects

40 - Pattern Objects Match Method Exersize

41 - Pattern Objects Match Method Exersize Solution

42 - Pattern Objects Match Method Vs Search Method

43 - Pattern Objects Finditer Method

44 - Pattern Objects Finditer Method Exersize Solution

5 - More Meta CharactersRegular Expressions

45 - Links for the Courses Materials and Codes.html

46 - Meta Characters Logical Or

47 - Meta Characters Beginning And End Patterns

48 - Meta Characters Paranthesis

6 - String ModificationRegular Expressions

49 - Links for the Courses Materials and Codes.html

50 - String Modification

51 - Word Tokenizer Using Split Method

52 - Sub Method Exercise

53 - Sub Method Exercise Solution

7 - Words and TokensText Preprocessing

54 - Links for the Courses Materials and Codes.html

55 - What Is A Word

56 - Definition Of Word Is Task Dependent

57 - Vocabulary And Corpus

58 - Tokens

59 - Tokenization In Spacy

8 - Sentiment ClassificationText Preprocessing

60 - Links for the Courses Materials and Codes.html

61 - Yelp Reviews Classification Mini Project Introduction

62 - Yelp Reviews Classification Mini Project Vocabulary Initialization

63 - Yelp Reviews Classification Mini Project Adding Tokens To Vocabulary

64 - Yelp Reviews Classification Mini Project Look Up Functions In Vocabulary

65 - Yelp Reviews Classification Mini Project Building Vocabulary From Data

66 - Yelp Reviews Classification Mini Project One Hot Encoding

67 - Yelp Reviews Classification Mini Project One Hot Encoding Implementation

68 - Yelp Reviews Classification Mini Project Encoding Documents

69 - Yelp Reviews Classification Mini Project Encoding Documents Implementation

70 - Yelp Reviews Classification Mini Project Train Test Splits

71 - Yelp Reviews Classification Mini Project Featurecomputation

72 - Yelp Reviews Classification Mini Project Classification

9 - Language Independent TokenizationText Preprocessing

73 - Links for the Courses Materials and Codes.html

74 - Tokenization In Detial Introduction

75 - Tokenization Is Hard

76 - Tokenization Byte Pair Encoding

77 - Tokenization Byte Pair Encoding Example

78 - Tokenization Byte Pair Encoding On Test Data

79 - Tokenization Byte Pair Encoding Implementation Getpaircounts

80 - Tokenization Byte Pair Encoding Implementation Mergeincorpus

81 - Tokenization Byte Pair Encoding Implementation BFE Training

82 - Tokenization Byte Pair Encoding Implementation BFE Encoding

83 - Tokenization Byte Pair Encoding Implementation BFE Encoding One Pair

84 - Tokenization Byte Pair Encoding Implementation BFE Encoding One Pair 1

10 - Text NomalizationText Preprocessing

85 - Links for the Courses Materials and Codes.html

86 - Word Normalization Case Folding

87 - Word Normalization Lematization

88 - Word Normalization Stemming

89 - Word Normalization Sentence Segmentation

11 - String Matching and Spelling CorrectionText Preprocessing

90 - Links for the Courses Materials and Codes.html

91 - Spelling Correction Minimum Edit Distance Intro

92 - Spelling Correction Minimum Edit Distance Example

93 - Spelling Correction Minimum Edit Distance Table Filling

94 - Spelling Correction Minimum Edit Distance Dynamic Programming

95 - Spelling Correction Minimum Edit Distance Psudocode

96 - Spelling Correction Minimum Edit Distance Implementation

97 - Spelling Correction Minimum Edit Distance Implementation Bugfixing

98 - Spelling Correction Implementation

12 - Language Modeling

99 - Links for the Courses Materials and Codes.html

100 - What Is A Language Model

101 - Language Model Formal Definition

102 - Language Model Curse Of Dimensionality

103 - Language Model Markov Assumption And NGrams

104 - Language Model Implementation Setup

105 - Language Model Implementation Ngrams Function

106 - Language Model Implementation Update Counts Function

107 - Language Model Implementation Probability Model Funciton

108 - Language Model Implementation Reading Corpus

109 - Language Model Implementation Sampling Text

13 - Topic Modelling with Word and Document Representations

110 - Links for the Courses Materials and Codes.html

111 - One Hot Vectors

112 - One Hot Vectors Implementaton

113 - One Hot Vectors Limitations

114 - One Hot Vectors Uses As Target Labeling

115 - Term Frequency For Document Representations

116 - Term Frequency For Document Representations Implementations

117 - Term Frequency For Word Representations

118 - TFIDF For Document Representations

119 - TFIDF For Document Representations Implementation Reading Corpus

120 - TFIDF For Document Representations Implementation Computing Document Frequenc

121 - TFIDF For Document Representations Implementation Computing TFIDF

122 - Topic Modeling With TFIDF 1

123 - Topic Modeling With TFIDF 3

124 - Topic Modeling With TFIDF 4

125 - Topic Modeling With TFIDF 5

126 - Topic Modeling With Gensim

14 - Word Embeddings LSI

127 - Links for the Courses Materials and Codes.html

128 - Word Cooccurrence Matrix

129 - Word Cooccurrence Matrix vs Documentterm Matrix

130 - Word Cooccurrence Matrix Implementation Preparing Data

131 - Word Cooccurrence Matrix Implementation Preparing Data 2

132 - Word Cooccurrence Matrix Implementation Preparing Data Getting Vocabulary

133 - Word Cooccurrence Matrix Implementation Final Function

134 - Word Cooccurrence Matrix Implementation Handling Memory Issues On Large Corp

135 - Word Cooccurrence Matrix Sparsity

136 - Word Cooccurrence Matrix Positive Point Wise Mutual Information PPMI

137 - PCA For Dense Embeddings

138 - Latent Semantic Analysis

139 - Latent Semantic Analysis Implementation

15 - Word Semantics

140 - Links for the Courses Materials and Codes.html

141 - Cosine Similarity

142 - Cosine Similarity Geting Norms Of Vectors

143 - Cosine Similarity Normalizing Vectors

144 - Cosine Similarity With More Than One Vectors

145 - Cosine Similarity Getting Most Similar Words In The Vocabulary

146 - Cosine Similarity Getting Most Similar Words In The Vocabulary Fixingbug Of D

147 - Cosine Similarity Word2Vec Embeddings

148 - Words Analogies

149 - Words Analogies Implemenation 1

150 - Words Analogies Implemenation 2

151 - Words Visualizations

152 - Words Visualizations Implementaion

153 - Words Visualizations Implementaion 2

16 - Word2vecOptional

154 - Links for the Courses Materials and Codes.html

155 - Static And Dynamic Embeddings

156 - Self Supervision

157 - Word2Vec Algorithm Abstract

158 - Word2Vec Why Negative Sampling

159 - Word2Vec What Is Skip Gram

160 - Word2Vec How To Define Probability Law

161 - Word2Vec Sigmoid

162 - Word2Vec Formalizing Loss Function

163 - Word2Vec Loss Function

164 - Word2Vec Gradient Descent Step

165 - Word2Vec Implemenation Preparing Data

166 - Word2Vec Implemenation Gradient Step

167 - Word2Vec Implemenation Driver Function

17 - Need of Deep Learning for NLPNLP with Deep Learning DNN

168 - Links for the Courses Materials and Codes.html

169 - Why RNNs For NLP

170 - Pytorch Installation And Tensors Introduction

171 - Automatic Diffrenciation Pytorch

18 - IntroductionNLP with Deep Learning DNN

172 - Links for the Courses Materials and Codes.html

173 - Why DNNs In Machine Learning

174 - Representational Power And Data Utilization Capacity Of DNN

175 - Perceptron

176 - Perceptron Implementation

177 - DNN Architecture

178 - DNN Forwardstep Implementation

179 - DNN Why Activation Function Is Required

180 - DNN Properties Of Activation Function

181 - DNN Activation Functions In Pytorch

182 - DNN What Is Loss Function

183 - DNN Loss Function In Pytorch

19 - TrainingNLP with Deep Learning DNN

184 - Links for the Courses Materials and Codes.html

185 - DNN Gradient Descent

186 - DNN Gradient Descent Implementation

187 - DNN Gradient Descent Stochastic Batch Minibatch

188 - DNN Gradient Descent Summary

189 - DNN Implemenation Gradient Step

190 - DNN Implemenation Stochastic Gradient Descent

191 - DNN Implemenation Batch Gradient Descent

192 - DNN Implemenation Minibatch Gradient Descent

193 - DNN Implemenation In Pytorch

20 - Hyper parametersNLP with Deep Learning DNN

194 - Links for the Courses Materials and Codes.html

195 - DNN Weights Initializations

196 - DNN Learning Rate

197 - DNN Batch Normalization

198 - DNN Batch Normalization Implementation

199 - DNN Optimizations

200 - DNN Dropout

201 - DNN Dropout In Pytorch

202 - DNN Early Stopping

203 - DNN Hyperparameters

204 - DNN Pytorch CIFAR10 Example

21 - IntroductionNLP with Deep Learning RNN

205 - Links for the Courses Materials and Codes.html

206 - What Is RNN

207 - Understanding RNN With A Simple Example

208 - RNN Applications Human Activity Recognition

209 - RNN Applications Image Captioning

210 - RNN Applications Machine Translation

211 - RNN Applications Speech Recognition Stock Price Prediction

212 - RNN Models

22 - Miniproject Language ModellingNLP with Deep Learning RNN

213 - Links for the Courses Materials and Codes.html

214 - Language Modeling Next Word Prediction

215 - Language Modeling Next Word Prediction Vocabulary Index

216 - Language Modeling Next Word Prediction Vocabulary Index Embeddings

217 - Language Modeling Next Word Prediction Rnn Architecture

218 - Language Modeling Next Word Prediction Python 1

219 - Language Modeling Next Word Prediction Python 2

220 - Language Modeling Next Word Prediction Python 3

221 - Language Modeling Next Word Prediction Python 4

222 - Language Modeling Next Word Prediction Python 5

223 - Language Modeling Next Word Prediction Python 6

23 - Miniproject Sentiment ClassificationNLP with Deep Learning RNN

224 - Links for the Courses Materials and Codes.html

225 - Vocabulary Implementation

226 - Vocabulary Implementation Helpers

227 - Vocabulary Implementation From File

228 - Vectorizer

229 - RNN Setup

230 - RNN Setup 1

24 - RNN in PyTorchNLP with Deep Learning RNN

231 - Links for the Courses Materials and Codes.html

232 - RNN In Pytorch Introduction

233 - RNN In Pytorch Embedding Layer

234 - RNN In Pytorch Nn Rnn

235 - RNN In Pytorch Output Shapes

236 - RNN In Pytorch Gatedunits

237 - RNN In Pytorch Gatedunits GRU LSTM

238 - RNN In Pytorch Bidirectional RNN

239 - RNN In Pytorch Bidirectional RNN Output Shapes

240 - RNN In Pytorch Bidirectional RNN Output Shapes Seperation

241 - RNN In Pytorch Example

25 - Advanced RNN modelsNLP with Deep Learning RNN

242 - Links for the Courses Materials and Codes.html

243 - RNN Encoder Decoder

244 - RNN Attention

26 - Neural Machine Translation

245 - Links for the Courses Materials and Codes.html

246 - Introduction To Dataset And Packages

247 - Implementing Language Class

248 - Testing Language Class And Implementing Normalization

249 - Reading Datafile

250 - Reading Building Vocabulary

251 - EncoderRNN

252 - DecoderRNN

253 - DecoderRNN Forward Step

254 - DecoderRNN Helper Functions

255 - Training Module

256 - Stochastic Gradient Descent

257 - NMT Training

258 - NMT Evaluation

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