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种子名称： [GigaCourse.Com] Udemy - Machine Learning Natural Language Processing in Python (V2)
文件类型： 视频
文件数目： 153个文件
文件大小： 6.59 GB
收录时间： 2023-3-2 10:32
已经下载： 3次
资源热度： 212
最近下载： 2024-12-28 00:23

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[GigaCourse.Com] Udemy - Machine Learning Natural Language Processing in Python (V2).torrent

01 - Introduction/001 Introduction and Outline.mp472.97MB

01 - Introduction/002 Are You Beginner, Intermediate, or Advanced All are OK!.mp426.66MB

02 - Getting Set Up/001 Get Your Hands Dirty, Practical Coding Experience, Data Links.mp443.56MB

02 - Getting Set Up/002 How to use Github & Extra Coding Tips (Optional).mp463.88MB

03 - Vector Models and Text Preprocessing/001 Vector Models & Text Preprocessing Intro.mp417.52MB

03 - Vector Models and Text Preprocessing/002 Basic Definitions for NLP.mp428.36MB

03 - Vector Models and Text Preprocessing/003 What is a Vector.mp448.93MB

03 - Vector Models and Text Preprocessing/004 Bag of Words.mp413.85MB

03 - Vector Models and Text Preprocessing/005 Count Vectorizer (Theory).mp457.43MB

03 - Vector Models and Text Preprocessing/006 Tokenization.mp473.51MB

03 - Vector Models and Text Preprocessing/007 Stopwords.mp423.44MB

03 - Vector Models and Text Preprocessing/008 Stemming and Lemmatization.mp457.92MB

03 - Vector Models and Text Preprocessing/009 Stemming and Lemmatization Demo.mp474.84MB

03 - Vector Models and Text Preprocessing/010 Count Vectorizer (Code).mp4101.98MB

03 - Vector Models and Text Preprocessing/011 Vector Similarity.mp445.11MB

03 - Vector Models and Text Preprocessing/012 TF-IDF (Theory).mp458.57MB

03 - Vector Models and Text Preprocessing/013 (Interactive) Recommender Exercise Prompt.mp413.38MB

03 - Vector Models and Text Preprocessing/014 TF-IDF (Code).mp4124.92MB

03 - Vector Models and Text Preprocessing/015 Word-to-Index Mapping.mp447.58MB

03 - Vector Models and Text Preprocessing/016 How to Build TF-IDF From Scratch.mp479.79MB

03 - Vector Models and Text Preprocessing/017 Neural Word Embeddings.mp445.54MB

03 - Vector Models and Text Preprocessing/018 Neural Word Embeddings Demo.mp466.84MB

03 - Vector Models and Text Preprocessing/019 Vector Models & Text Preprocessing Summary.mp420.85MB

03 - Vector Models and Text Preprocessing/020 Text Summarization Preview.mp46.28MB

03 - Vector Models and Text Preprocessing/021 How To Do NLP In Other Languages.mp455.96MB

03 - Vector Models and Text Preprocessing/022 Suggestion Box.mp427.16MB

04 - Probabilistic Models (Introduction)/001 Probabilistic Models (Introduction).mp426.91MB

05 - Markov Models (Intermediate)/001 Markov Models Section Introduction.mp413.09MB

05 - Markov Models (Intermediate)/002 The Markov Property.mp432.25MB

05 - Markov Models (Intermediate)/003 The Markov Model.mp445.84MB

05 - Markov Models (Intermediate)/004 Probability Smoothing and Log-Probabilities.mp434.06MB

05 - Markov Models (Intermediate)/005 Building a Text Classifier (Theory).mp428.92MB

05 - Markov Models (Intermediate)/006 Building a Text Classifier (Exercise Prompt).mp429.36MB

05 - Markov Models (Intermediate)/007 Building a Text Classifier (Code pt 1).mp457.68MB

05 - Markov Models (Intermediate)/008 Building a Text Classifier (Code pt 2).mp472.22MB

05 - Markov Models (Intermediate)/009 Language Model (Theory).mp444.96MB

05 - Markov Models (Intermediate)/010 Language Model (Exercise Prompt).mp428.8MB

05 - Markov Models (Intermediate)/011 Language Model (Code pt 1).mp462.83MB

05 - Markov Models (Intermediate)/012 Language Model (Code pt 2).mp452.43MB

05 - Markov Models (Intermediate)/013 Markov Models Section Summary.mp415.56MB

06 - Article Spinner (Intermediate)/001 Article Spinning - Problem Description.mp441.92MB

06 - Article Spinner (Intermediate)/002 Article Spinning - N-Gram Approach.mp415.92MB

06 - Article Spinner (Intermediate)/003 Article Spinner Exercise Prompt.mp424.62MB

06 - Article Spinner (Intermediate)/004 Article Spinner in Python (pt 1).mp495.89MB

06 - Article Spinner (Intermediate)/005 Article Spinner in Python (pt 2).mp475.37MB

06 - Article Spinner (Intermediate)/006 Case Study Article Spinning Gone Wrong.mp428.23MB

07 - Cipher Decryption (Advanced)/001 Section Introduction.mp426.32MB

07 - Cipher Decryption (Advanced)/002 Ciphers.mp417.21MB

07 - Cipher Decryption (Advanced)/003 Language Models (Review).mp465.53MB

07 - Cipher Decryption (Advanced)/004 Genetic Algorithms.mp4105.16MB

07 - Cipher Decryption (Advanced)/005 Code Preparation.mp420.63MB

07 - Cipher Decryption (Advanced)/006 Code pt 1.mp415.98MB

07 - Cipher Decryption (Advanced)/007 Code pt 2.mp439.13MB

07 - Cipher Decryption (Advanced)/008 Code pt 3.mp429.54MB

07 - Cipher Decryption (Advanced)/009 Code pt 4.mp425.62MB

07 - Cipher Decryption (Advanced)/010 Code pt 5.mp440.96MB

07 - Cipher Decryption (Advanced)/011 Code pt 6.mp439.4MB

07 - Cipher Decryption (Advanced)/012 Cipher Decryption - Additional Discussion.mp414.7MB

07 - Cipher Decryption (Advanced)/013 Section Conclusion.mp424.24MB

08 - Machine Learning Models (Introduction)/001 Machine Learning Models (Introduction).mp429.6MB

09 - Spam Detection/001 Spam Detection - Problem Description.mp431.33MB

09 - Spam Detection/002 Naive Bayes Intuition.mp451.33MB

09 - Spam Detection/003 Spam Detection - Exercise Prompt.mp48.73MB

09 - Spam Detection/004 Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).mp460.21MB

09 - Spam Detection/005 Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).mp453.97MB

09 - Spam Detection/006 Spam Detection in Python.mp4107.6MB

10 - Sentiment Analysis/001 Sentiment Analysis - Problem Description.mp442.7MB

10 - Sentiment Analysis/002 Logistic Regression Intuition (pt 1).mp463.57MB

10 - Sentiment Analysis/003 Multiclass Logistic Regression (pt 2).mp423.61MB

10 - Sentiment Analysis/004 Logistic Regression Training and Interpretation (pt 3).mp439.63MB

10 - Sentiment Analysis/005 Sentiment Analysis - Exercise Prompt.mp416.55MB

10 - Sentiment Analysis/006 Sentiment Analysis in Python (pt 1).mp463.15MB

10 - Sentiment Analysis/007 Sentiment Analysis in Python (pt 2).mp451.96MB

11 - Text Summarization/001 Text Summarization Section Introduction.mp425.75MB

11 - Text Summarization/002 Text Summarization Using Vectors.mp425.77MB

11 - Text Summarization/003 Text Summarization Exercise Prompt.mp48.1MB

11 - Text Summarization/004 Text Summarization in Python.mp478.15MB

11 - Text Summarization/005 TextRank Intuition.mp445.92MB

11 - Text Summarization/006 TextRank - How It Really Works (Advanced).mp449.31MB

11 - Text Summarization/007 TextRank Exercise Prompt (Advanced).mp47.47MB

11 - Text Summarization/008 TextRank in Python (Advanced).mp482.3MB

11 - Text Summarization/009 Text Summarization in Python - The Easy Way (Beginner).mp445.17MB

11 - Text Summarization/010 Text Summarization Section Summary.mp420.1MB

12 - Topic Modeling/001 Topic Modeling Section Introduction.mp417.04MB

12 - Topic Modeling/002 Latent Dirichlet Allocation (LDA) - Essentials.mp455.18MB

12 - Topic Modeling/003 LDA - Code Preparation.mp414.51MB

12 - Topic Modeling/004 LDA - Maybe Useful Picture (Optional).mp48.98MB

12 - Topic Modeling/005 Latent Dirichlet Allocation (LDA) - Intuition (Advanced).mp460.18MB

12 - Topic Modeling/006 Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.mp472.38MB

12 - Topic Modeling/007 Non-Negative Matrix Factorization (NMF) Intuition.mp452.48MB

12 - Topic Modeling/008 Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.mp436.03MB

12 - Topic Modeling/009 Topic Modeling Section Summary.mp49.81MB

13 - Latent Semantic Analysis (Latent Semantic Indexing)/001 LSA LSI Section Introduction.mp420.95MB

13 - Latent Semantic Analysis (Latent Semantic Indexing)/002 SVD (Singular Value Decomposition) Intuition.mp481.84MB

13 - Latent Semantic Analysis (Latent Semantic Indexing)/003 LSA LSI Applying SVD to NLP.mp434.42MB

13 - Latent Semantic Analysis (Latent Semantic Indexing)/004 Latent Semantic Analysis Latent Semantic Indexing in Python.mp457.55MB

13 - Latent Semantic Analysis (Latent Semantic Indexing)/005 LSA LSI Exercises.mp429.05MB

14 - Deep Learning (Introduction)/001 Deep Learning Introduction (Intermediate-Advanced).mp424.52MB

15 - The Neuron/001 The Neuron - Section Introduction.mp411.01MB

15 - The Neuron/002 Fitting a Line.mp468.61MB

15 - The Neuron/003 Classification Code Preparation.mp432.88MB

15 - The Neuron/004 Text Classification in Tensorflow.mp481.66MB

15 - The Neuron/005 The Neuron.mp445.25MB

15 - The Neuron/006 How does a model learn.mp451.58MB

15 - The Neuron/007 The Neuron - Section Summary.mp410.31MB

16 - Feedforward Artificial Neural Networks/001 ANN - Section Introduction.mp438.63MB

16 - Feedforward Artificial Neural Networks/002 Forward Propagation.mp446.72MB

16 - Feedforward Artificial Neural Networks/003 The Geometrical Picture.mp456.53MB

16 - Feedforward Artificial Neural Networks/004 Activation Functions.mp489.31MB

16 - Feedforward Artificial Neural Networks/005 Multiclass Classification.mp444.41MB

16 - Feedforward Artificial Neural Networks/006 ANN Code Preparation.mp420.14MB

16 - Feedforward Artificial Neural Networks/007 Text Classification ANN in Tensorflow.mp436.12MB

16 - Feedforward Artificial Neural Networks/008 Text Preprocessing Code Preparation.mp449.99MB

16 - Feedforward Artificial Neural Networks/009 Text Preprocessing in Tensorflow.mp430.93MB

16 - Feedforward Artificial Neural Networks/010 Embeddings.mp442.28MB

16 - Feedforward Artificial Neural Networks/011 CBOW (Advanced).mp415.77MB

16 - Feedforward Artificial Neural Networks/012 CBOW Exercise Prompt.mp45.02MB

16 - Feedforward Artificial Neural Networks/013 CBOW in Tensorflow (Advanced).mp4117.55MB

16 - Feedforward Artificial Neural Networks/014 ANN - Section Summary.mp47.6MB

16 - Feedforward Artificial Neural Networks/015 Aside How to Choose Hyperparameters (Optional).mp438.07MB

17 - Convolutional Neural Networks/001 CNN - Section Introduction.mp425.62MB

17 - Convolutional Neural Networks/002 What is Convolution.mp479.86MB

17 - Convolutional Neural Networks/003 What is Convolution (Pattern Matching).mp424.62MB

17 - Convolutional Neural Networks/004 What is Convolution (Weight Sharing).mp428.83MB

17 - Convolutional Neural Networks/005 Convolution on Color Images.mp475.19MB

17 - Convolutional Neural Networks/006 CNN Architecture.mp489.28MB

17 - Convolutional Neural Networks/007 CNNs for Text.mp440.48MB

17 - Convolutional Neural Networks/008 Convolutional Neural Network for NLP in Tensorflow.mp442.04MB

17 - Convolutional Neural Networks/009 CNN - Section Summary.mp48.19MB

18 - Recurrent Neural Networks/001 RNN - Section Introduction.mp420.9MB

18 - Recurrent Neural Networks/002 Simple RNN Elman Unit (pt 1).mp440.83MB

18 - Recurrent Neural Networks/003 Simple RNN Elman Unit (pt 2).mp441.18MB

18 - Recurrent Neural Networks/004 RNN Code Preparation.mp442.14MB

18 - Recurrent Neural Networks/005 RNNs Paying Attention to Shapes.mp457.17MB

18 - Recurrent Neural Networks/006 GRU and LSTM (pt 1).mp482.25MB

18 - Recurrent Neural Networks/007 GRU and LSTM (pt 2).mp450.34MB

18 - Recurrent Neural Networks/008 RNN for Text Classification in Tensorflow.mp445.91MB

18 - Recurrent Neural Networks/009 Parts-of-Speech (POS) Tagging in Tensorflow.mp4145.1MB

18 - Recurrent Neural Networks/010 Named Entity Recognition (NER) in Tensorflow.mp431.54MB

18 - Recurrent Neural Networks/011 Exercise Return to CNNs (Advanced).mp414.55MB

18 - Recurrent Neural Networks/012 RNN - Section Summary.mp49.09MB

19 - Setting Up Your Environment FAQ/001 Anaconda Environment Setup.mp452.63MB

19 - Setting Up Your Environment FAQ/002 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp450.9MB

20 - Extra Help With Python Coding for Beginners FAQ/001 Where to get the code, notebooks, and data.mp417.72MB

20 - Extra Help With Python Coding for Beginners FAQ/002 How to Code by Yourself (part 1).mp471.86MB

20 - Extra Help With Python Coding for Beginners FAQ/003 How to Code by Yourself (part 2).mp449.15MB

20 - Extra Help With Python Coding for Beginners FAQ/004 Proof that using Jupyter Notebook is the same as not using it.mp469.42MB

21 - Effective Learning Strategies for Machine Learning FAQ/001 How to Succeed in this Course (Long Version).mp417.87MB

21 - Effective Learning Strategies for Machine Learning FAQ/002 Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp438.95MB

21 - Effective Learning Strategies for Machine Learning FAQ/003 Machine Learning and AI Prerequisite Roadmap (pt 1).mp479.67MB

21 - Effective Learning Strategies for Machine Learning FAQ/004 Machine Learning and AI Prerequisite Roadmap (pt 2).mp4108.15MB

22 - Appendix FAQ Finale/001 What is the Appendix.mp416.39MB

22 - Appendix FAQ Finale/002 BONUS.mp439.88MB