FreeCourseSite com Udemy Machine Learning Natural Language Processing in Python V2

FreeCourseSite com Udemy Machine Learning Natural Language Processing in Python V2

Name	[FreeCourseSite.com] Udemy - Machine Learning Natural Language Processing in Python (V2)	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	7.2 GB
Total Files	326
Last Seen	2025-05-06 00:38
Hash	BE261FE5DA17AC84A4A3103CABB3C8D871AC10B9

/0. Websites you may like/
[CourseClub.Me].url	0.1 KB
[FreeCourseSite.com].url	0.1 KB
[GigaCourse.Com].url	0.0 KB
/1. Introduction/
1. Introduction and Outline.mp4	76.5 MB
1. Introduction and Outline.srt	15.8 KB
2. Are You Beginner, Intermediate, or Advanced All are OK!.mp4	28.0 MB
2. Are You Beginner, Intermediate, or Advanced All are OK!.srt	7.4 KB
/10. Sentiment Analysis/
1. Sentiment Analysis - Problem Description.mp4	44.8 MB
1. Sentiment Analysis - Problem Description.srt	10.1 KB
2. Logistic Regression Intuition (pt 1).mp4	66.7 MB
2. Logistic Regression Intuition (pt 1).srt	23.1 KB
3. Multiclass Logistic Regression (pt 2).mp4	24.8 MB
3. Multiclass Logistic Regression (pt 2).srt	8.7 KB
4. Logistic Regression Training and Interpretation (pt 3).mp4	41.6 MB
4. Logistic Regression Training and Interpretation (pt 3).srt	11.1 KB
5. Sentiment Analysis - Exercise Prompt.mp4	17.4 MB
5. Sentiment Analysis - Exercise Prompt.srt	5.2 KB
6. Sentiment Analysis in Python (pt 1).mp4	66.2 MB
6. Sentiment Analysis in Python (pt 1).srt	11.9 KB
7. Sentiment Analysis in Python (pt 2).mp4	54.5 MB
7. Sentiment Analysis in Python (pt 2).srt	10.0 KB
/11. Text Summarization/
1. Text Summarization Section Introduction.mp4	27.0 MB
1. Text Summarization Section Introduction.srt	7.7 KB
10. Text Summarization Section Summary.mp4	21.1 MB
10. Text Summarization Section Summary.srt	4.5 KB
2. Text Summarization Using Vectors.mp4	27.0 MB
2. Text Summarization Using Vectors.srt	7.5 KB
3. Text Summarization Exercise Prompt.mp4	8.5 MB
3. Text Summarization Exercise Prompt.srt	2.4 KB
4. Text Summarization in Python.mp4	81.9 MB
4. Text Summarization in Python.srt	15.4 KB
5. TextRank Intuition.mp4	48.2 MB
5. TextRank Intuition.srt	11.2 KB
6. TextRank - How It Really Works (Advanced).mp4	51.7 MB
6. TextRank - How It Really Works (Advanced).srt	13.8 KB
7. TextRank Exercise Prompt (Advanced).mp4	7.8 MB
7. TextRank Exercise Prompt (Advanced).srt	1.8 KB
8. TextRank in Python (Advanced).mp4	86.3 MB
8. TextRank in Python (Advanced).srt	17.5 KB
9. Text Summarization in Python - The Easy Way (Beginner).mp4	47.4 MB
9. Text Summarization in Python - The Easy Way (Beginner).srt	8.0 KB
/12. Topic Modeling/
1. Topic Modeling Section Introduction.mp4	17.9 MB
1. Topic Modeling Section Introduction.srt	4.2 KB
2. Latent Dirichlet Allocation (LDA) - Essentials.mp4	57.9 MB
2. Latent Dirichlet Allocation (LDA) - Essentials.srt	15.5 KB
3. LDA - Code Preparation.mp4	15.2 MB
3. LDA - Code Preparation.srt	5.0 KB
4. LDA - Maybe Useful Picture (Optional).mp4	9.4 MB
4. LDA - Maybe Useful Picture (Optional).srt	2.6 KB
5. Latent Dirichlet Allocation (LDA) - Intuition (Advanced).mp4	63.1 MB
5. Latent Dirichlet Allocation (LDA) - Intuition (Advanced).srt	20.7 KB
6. Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.mp4	75.9 MB
6. Topic Modeling with Latent Dirichlet Allocation (LDA) in Python.srt	13.6 KB
7. Non-Negative Matrix Factorization (NMF) Intuition.mp4	55.0 MB
7. Non-Negative Matrix Factorization (NMF) Intuition.srt	14.1 KB
8. Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.mp4	37.8 MB
8. Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python.srt	5.0 KB
9. Topic Modeling Section Summary.mp4	10.3 MB
9. Topic Modeling Section Summary.srt	2.0 KB
/13. Latent Semantic Analysis (Latent Semantic Indexing)/
1. LSA LSI Section Introduction.mp4	22.0 MB
1. LSA LSI Section Introduction.srt	5.3 KB
2. SVD (Singular Value Decomposition) Intuition.mp4	85.8 MB
2. SVD (Singular Value Decomposition) Intuition.srt	15.8 KB
3. LSA LSI Applying SVD to NLP.mp4	36.1 MB
3. LSA LSI Applying SVD to NLP.srt	10.5 KB
4. Latent Semantic Analysis Latent Semantic Indexing in Python.mp4	60.4 MB
4. Latent Semantic Analysis Latent Semantic Indexing in Python.srt	10.3 KB
5. LSA LSI Exercises.mp4	30.5 MB
5. LSA LSI Exercises.srt	7.5 KB
/14. Deep Learning (Introduction)/
1. Deep Learning Introduction (Intermediate-Advanced).mp4	25.7 MB
1. Deep Learning Introduction (Intermediate-Advanced).srt	6.9 KB
/15. The Neuron/
1. The Neuron - Section Introduction.mp4	11.5 MB
1. The Neuron - Section Introduction.srt	3.0 KB
2. Fitting a Line.mp4	71.9 MB
2. Fitting a Line.srt	18.8 KB
3. Classification Code Preparation.mp4	34.5 MB
3. Classification Code Preparation.srt	9.7 KB
4. Text Classification in Tensorflow.mp4	85.6 MB
4. Text Classification in Tensorflow.srt	12.0 KB
5. The Neuron.mp4	47.4 MB
5. The Neuron.srt	13.0 KB
6. How does a model learn.mp4	54.1 MB
6. How does a model learn.srt	14.7 KB
7. The Neuron - Section Summary.mp4	10.8 MB
7. The Neuron - Section Summary.srt	2.2 KB
/16. Feedforward Artificial Neural Networks/
1. ANN - Section Introduction.mp4	40.5 MB
1. ANN - Section Introduction.srt	9.5 KB
10. Embeddings.mp4	44.3 MB
10. Embeddings.srt	12.9 KB
11. CBOW (Advanced).mp4	16.5 MB
11. CBOW (Advanced).srt	5.4 KB
12. CBOW Exercise Prompt.mp4	5.3 MB
12. CBOW Exercise Prompt.srt	1.0 KB
13. CBOW in Tensorflow (Advanced).mp4	123.3 MB
13. CBOW in Tensorflow (Advanced).srt	20.8 KB
14. ANN - Section Summary.mp4	8.0 MB
14. ANN - Section Summary.srt	2.0 KB
15. Aside How to Choose Hyperparameters (Optional).mp4	39.9 MB
15. Aside How to Choose Hyperparameters (Optional).srt	8.8 KB
2. Forward Propagation.mp4	49.0 MB
2. Forward Propagation.srt	12.9 KB
3. The Geometrical Picture.mp4	59.3 MB
3. The Geometrical Picture.srt	12.1 KB
4. Activation Functions.mp4	93.7 MB
4. Activation Functions.srt	23.5 KB
5. Multiclass Classification.mp4	46.6 MB
5. Multiclass Classification.srt	11.6 KB
6. ANN Code Preparation.mp4	21.1 MB
6. ANN Code Preparation.srt	6.1 KB
7. Text Classification ANN in Tensorflow.mp4	37.9 MB
7. Text Classification ANN in Tensorflow.srt	5.2 KB
8. Text Preprocessing Code Preparation.mp4	52.4 MB
8. Text Preprocessing Code Preparation.srt	15.2 KB
9. Text Preprocessing in Tensorflow.mp4	32.4 MB
9. Text Preprocessing in Tensorflow.srt	6.4 KB
/17. Convolutional Neural Networks/
1. CNN - Section Introduction.mp4	26.9 MB
1. CNN - Section Introduction.srt	6.1 KB
2. What is Convolution.mp4	83.7 MB
2. What is Convolution.srt	21.2 KB
3. What is Convolution (Pattern Matching).mp4	25.8 MB
3. What is Convolution (Pattern Matching).srt	7.1 KB
4. What is Convolution (Weight Sharing).mp4	31.3 MB
4. What is Convolution (Weight Sharing).srt	8.3 KB
5. Convolution on Color Images.mp4	78.9 MB
5. Convolution on Color Images.srt	21.4 KB
6. CNN Architecture.mp4	93.6 MB
6. CNN Architecture.srt	29.4 KB
7. CNNs for Text.mp4	42.5 MB
7. CNNs for Text.srt	10.0 KB
8. Convolutional Neural Network for NLP in Tensorflow.mp4	44.1 MB
8. Convolutional Neural Network for NLP in Tensorflow.srt	5.1 KB
9. CNN - Section Summary.mp4	8.6 MB
9. CNN - Section Summary.srt	1.7 KB
[CourseClub.Me].url	0.1 KB
[FreeCourseSite.com].url	0.1 KB
[GigaCourse.Com].url	0.0 KB
/18. Recurrent Neural Networks/
1. RNN - Section Introduction.mp4	21.9 MB
1. RNN - Section Introduction.srt	6.5 KB
10. Named Entity Recognition (NER) in Tensorflow.mp4	33.1 MB
10. Named Entity Recognition (NER) in Tensorflow.srt	6.3 KB
11. Exercise Return to CNNs (Advanced).mp4	15.3 MB
11. Exercise Return to CNNs (Advanced).srt	4.2 KB
12. RNN - Section Summary.mp4	9.5 MB
12. RNN - Section Summary.srt	2.4 KB
2. Simple RNN Elman Unit (pt 1).mp4	42.8 MB
2. Simple RNN Elman Unit (pt 1).srt	11.8 KB
3. Simple RNN Elman Unit (pt 2).mp4	43.2 MB
3. Simple RNN Elman Unit (pt 2).srt	13.2 KB
4. RNN Code Preparation.mp4	44.2 MB
4. RNN Code Preparation.srt	12.9 KB
5. RNNs Paying Attention to Shapes.mp4	59.9 MB
5. RNNs Paying Attention to Shapes.srt	10.4 KB
6. GRU and LSTM (pt 1).mp4	86.3 MB
6. GRU and LSTM (pt 1).srt	23.8 KB
7. GRU and LSTM (pt 2).mp4	52.8 MB
7. GRU and LSTM (pt 2).srt	15.5 KB
8. RNN for Text Classification in Tensorflow.mp4	48.2 MB
8. RNN for Text Classification in Tensorflow.srt	5.7 KB
9. Parts-of-Speech (POS) Tagging in Tensorflow.mp4	152.2 MB
9. Parts-of-Speech (POS) Tagging in Tensorflow.srt	23.2 KB
/19. Setting Up Your Environment FAQ/
1. Pre-Installation Check.mp4	23.9 MB
1. Pre-Installation Check.srt	6.8 KB
2. Anaconda Environment Setup.mp4	55.2 MB
2. Anaconda Environment Setup.srt	20.6 KB
3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4	53.4 MB
3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt	15.0 KB
/2. Getting Set Up/
1. Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4	45.7 MB
1. Get Your Hands Dirty, Practical Coding Experience, Data Links.srt	12.3 KB
1.1 Data Links.html	0.2 KB
1.2 Github Link.html	0.1 KB
2. How to use Github & Extra Coding Tips (Optional).mp4	67.0 MB
2. How to use Github & Extra Coding Tips (Optional).srt	16.1 KB
3. Where to get the code, notebooks, and data.mp4	18.6 MB
3. Where to get the code, notebooks, and data.srt	4.4 KB
3.1 Code Link.html	0.1 KB
3.2 Data Links.html	0.2 KB
3.3 Github Link.html	0.1 KB
4. How to Succeed in This Course.mp4	43.2 MB
4. How to Succeed in This Course.srt	13.3 KB
5. Temporary 403 Errors.mp4	23.1 MB
5. Temporary 403 Errors.srt	3.8 KB
/20. Extra Help With Python Coding for Beginners FAQ/
1. How to Code by Yourself (part 1).mp4	75.3 MB
1. How to Code by Yourself (part 1).srt	23.2 KB
2. How to Code by Yourself (part 2).mp4	51.6 MB
2. How to Code by Yourself (part 2).srt	13.6 KB
3. Proof that using Jupyter Notebook is the same as not using it.mp4	72.8 MB
3. Proof that using Jupyter Notebook is the same as not using it.srt	14.7 KB
/21. Effective Learning Strategies for Machine Learning FAQ/
1. How to Succeed in this Course (Long Version).mp4	18.7 MB
1. How to Succeed in this Course (Long Version).srt	14.9 KB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4	40.9 MB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt	33.2 KB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4	83.5 MB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).srt	17.0 KB
4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4	113.4 MB
4. Machine Learning and AI Prerequisite Roadmap (pt 2).srt	24.2 KB
/22. Appendix FAQ Finale/
1. What is the Appendix.mp4	17.2 MB
1. What is the Appendix.srt	3.9 KB
2. BONUS.mp4	41.8 MB
2. BONUS.srt	8.1 KB
/3. Vector Models and Text Preprocessing/
1. Vector Models & Text Preprocessing Intro.mp4	18.4 MB
1. Vector Models & Text Preprocessing Intro.srt	5.1 KB
10. Count Vectorizer (Code).mp4	106.9 MB
10. Count Vectorizer (Code).srt	19.6 KB
11. Vector Similarity.mp4	47.3 MB
11. Vector Similarity.srt	15.5 KB
12. TF-IDF (Theory).mp4	61.4 MB
12. TF-IDF (Theory).srt	18.7 KB
13. (Interactive) Recommender Exercise Prompt.mp4	14.0 MB
13. (Interactive) Recommender Exercise Prompt.srt	3.3 KB
14. TF-IDF (Code).mp4	131.0 MB
14. TF-IDF (Code).srt	25.4 KB
15. Word-to-Index Mapping.mp4	49.9 MB
15. Word-to-Index Mapping.srt	15.2 KB
16. How to Build TF-IDF From Scratch.mp4	83.7 MB
16. How to Build TF-IDF From Scratch.srt	19.0 KB
17. Neural Word Embeddings.mp4	47.8 MB
17. Neural Word Embeddings.srt	13.8 KB
18. Neural Word Embeddings Demo.mp4	70.1 MB
18. Neural Word Embeddings Demo.srt	13.0 KB
19. Vector Models & Text Preprocessing Summary.mp4	21.9 MB
19. Vector Models & Text Preprocessing Summary.srt	4.9 KB
2. Basic Definitions for NLP.mp4	29.7 MB
2. Basic Definitions for NLP.srt	6.8 KB
20. Text Summarization Preview.mp4	6.6 MB
20. Text Summarization Preview.srt	1.7 KB
21. How To Do NLP In Other Languages.mp4	58.7 MB
21. How To Do NLP In Other Languages.srt	14.9 KB
22. Suggestion Box.mp4	28.5 MB
22. Suggestion Box.srt	4.9 KB
3. What is a Vector.mp4	51.3 MB
3. What is a Vector.srt	15.2 KB
4. Bag of Words.mp4	14.5 MB
4. Bag of Words.srt	3.2 KB
5. Count Vectorizer (Theory).mp4	60.2 MB
5. Count Vectorizer (Theory).srt	19.6 KB
6. Tokenization.mp4	77.1 MB
6. Tokenization.srt	20.3 KB
7. Stopwords.mp4	24.6 MB
7. Stopwords.srt	6.5 KB
8. Stemming and Lemmatization.mp4	60.7 MB
8. Stemming and Lemmatization.srt	16.2 KB
9. Stemming and Lemmatization Demo.mp4	78.5 MB
9. Stemming and Lemmatization Demo.srt	14.2 KB
/4. Probabilistic Models (Introduction)/
1. Probabilistic Models (Introduction).mp4	28.2 MB
1. Probabilistic Models (Introduction).srt	6.4 KB
/5. Markov Models (Intermediate)/
1. Markov Models Section Introduction.mp4	13.7 MB
1. Markov Models Section Introduction.srt	3.5 KB
10. Language Model (Exercise Prompt).mp4	30.2 MB
10. Language Model (Exercise Prompt).srt	9.2 KB
11. Language Model (Code pt 1).mp4	65.9 MB
11. Language Model (Code pt 1).srt	13.5 KB
12. Language Model (Code pt 2).mp4	55.0 MB
12. Language Model (Code pt 2).srt	11.6 KB
13. Markov Models Section Summary.mp4	16.3 MB
13. Markov Models Section Summary.srt	4.1 KB
2. The Markov Property.mp4	33.8 MB
2. The Markov Property.srt	9.7 KB
3. The Markov Model.mp4	48.1 MB
3. The Markov Model.srt	16.9 KB
4. Probability Smoothing and Log-Probabilities.mp4	35.7 MB
4. Probability Smoothing and Log-Probabilities.srt	10.5 KB
5. Building a Text Classifier (Theory).mp4	30.3 MB
5. Building a Text Classifier (Theory).srt	9.7 KB
6. Building a Text Classifier (Exercise Prompt).mp4	30.8 MB
6. Building a Text Classifier (Exercise Prompt).srt	9.0 KB
7. Building a Text Classifier (Code pt 1).mp4	60.5 MB
7. Building a Text Classifier (Code pt 1).srt	12.1 KB
8. Building a Text Classifier (Code pt 2).mp4	75.7 MB
8. Building a Text Classifier (Code pt 2).srt	14.1 KB
9. Language Model (Theory).mp4	47.1 MB
9. Language Model (Theory).srt	13.6 KB
[CourseClub.Me].url	0.1 KB
[FreeCourseSite.com].url	0.1 KB
[GigaCourse.Com].url	0.0 KB
/6. Article Spinner (Intermediate)/
1. Article Spinning - Problem Description.mp4	44.0 MB
1. Article Spinning - Problem Description.srt	11.0 KB
2. Article Spinning - N-Gram Approach.mp4	16.7 MB
2. Article Spinning - N-Gram Approach.srt	5.3 KB
3. Article Spinner Exercise Prompt.mp4	25.8 MB
3. Article Spinner Exercise Prompt.srt	7.8 KB
4. Article Spinner in Python (pt 1).mp4	100.6 MB
4. Article Spinner in Python (pt 1).srt	21.2 KB
5. Article Spinner in Python (pt 2).mp4	79.0 MB
5. Article Spinner in Python (pt 2).srt	12.7 KB
6. Case Study Article Spinning Gone Wrong.mp4	29.6 MB
6. Case Study Article Spinning Gone Wrong.srt	7.7 KB
/7. Cipher Decryption (Advanced)/
1. Section Introduction.mp4	27.6 MB
1. Section Introduction.srt	6.8 KB
10. Code pt 5.mp4	43.0 MB
10. Code pt 5.srt	9.0 KB
11. Code pt 6.mp4	41.3 MB
11. Code pt 6.srt	7.4 KB
12. Cipher Decryption - Additional Discussion.mp4	15.4 MB
12. Cipher Decryption - Additional Discussion.srt	4.2 KB
13. Section Conclusion.mp4	25.4 MB
13. Section Conclusion.srt	8.5 KB
2. Ciphers.mp4	18.1 MB
2. Ciphers.srt	4.9 KB
3. Language Models (Review).mp4	68.7 MB
3. Language Models (Review).srt	21.0 KB
4. Genetic Algorithms.mp4	110.3 MB
4. Genetic Algorithms.srt	29.9 KB
5. Code Preparation.mp4	21.6 MB
5. Code Preparation.srt	6.9 KB
6. Code pt 1.mp4	16.8 MB
6. Code pt 1.srt	4.2 KB
7. Code pt 2.mp4	41.0 MB
7. Code pt 2.srt	9.5 KB
8. Code pt 3.mp4	31.0 MB
8. Code pt 3.srt	6.3 KB
9. Code pt 4.mp4	26.9 MB
9. Code pt 4.srt	5.0 KB
/8. Machine Learning Models (Introduction)/
1. Machine Learning Models (Introduction).mp4	31.0 MB
1. Machine Learning Models (Introduction).srt	8.0 KB
/9. Spam Detection/
1. Spam Detection - Problem Description.mp4	32.9 MB
1. Spam Detection - Problem Description.srt	8.9 KB
2. Naive Bayes Intuition.mp4	53.8 MB
2. Naive Bayes Intuition.srt	15.6 KB
3. Spam Detection - Exercise Prompt.mp4	9.2 MB
3. Spam Detection - Exercise Prompt.srt	2.7 KB
4. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).mp4	63.1 MB
4. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 1).srt	17.2 KB
5. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).mp4	56.6 MB
5. Aside Class Imbalance, ROC, AUC, and F1 Score (pt 2).srt	14.8 KB
6. Spam Detection in Python.mp4	112.8 MB
6. Spam Detection in Python.srt	19.7 KB
Total files 326