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**AD-TEAM** · 5 hours ago

[Image: 537368816_que-es-udemy-analisis-opiniones.jpg]

9.22 GB | 24min 54s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English

Files Included :
1 -Introduction of the course.mp4 (53.24 MB)
2 -How to succeed in this course.mp4 (3.56 MB)
1 -Introduction of the section.mp4 (4.66 MB)
2 -Topic Modeling.mp4 (28.25 MB)
3 -Latent Dirichlet Allocation ( LDA ).mp4 (32.65 MB)
4 -Project01 Topic Modeling with LDA.mp4 (123.67 MB)
5 -Non Negative Matrix Factorization ( NMF ).mp4 (29.49 MB)
6 -Topic Modeling with NMF.mp4 (87.93 MB)
1 -1-Introduction of the section.mp4 (1.58 MB)
1 -Introduction of the section.mp4 (5.16 MB)
10 -MSE Loss Function.mp4 (14.19 MB)
11 -Cross Entropy Loss Function.mp4 (37.52 MB)
12 -Softmax Function.mp4 (35.51 MB)
2 -The Perceptron.mp4 (65.16 MB)
3 -Features, Weight and Activation Functions.mp4 (23.38 MB)
4 -Learning of Neural Network.mp4 (35.43 MB)
5 -Need of Activation Functions.mp4 (19.58 MB)
6 -Adding Activation Function to Neural Network.mp4 (16.54 MB)
7 -Sigmoid as an Activation Function.mp4 (34.37 MB)
8 -Hyperbolic Tangent Function.mp4 (25.65 MB)
9 -ReLU and Leaky ReLU.mp4 (23.13 MB)
1 -Introduction of the section.mp4 (4.32 MB)
2 -Code Preparation.mp4 (24.37 MB)
3 -Project01 Implementing Neural Network in TensorFlow Part-01.mp4 (62.27 MB)
4 -Project01 Implementing Neural Network in TensorFlow Part-02.mp4 (36.49 MB)
5 -Project02 Text Classification with Neural Network Part-01.mp4 (90.31 MB)
6 -Project02 Text Classification with Neural Network Part-02.mp4 (52.45 MB)
1 -Introduction of the section.mp4 (18.93 MB)
2 -One Hot Encoding.mp4 (23.34 MB)
3 -One Hot Encoding in Python.mp4 (23.34 MB)
4 -Co-occurrence Matrix - Word Embeddings Intuition.mp4 (125.69 MB)
1 -Introduction of the section.mp4 (38.34 MB)
10 -Project03 Find Analogies with Word2Vec.mp4 (71.12 MB)
11 -Text Classification using Word2Vec.mp4 (77.47 MB)
2 -Methods of Word Embeddings.mp4 (11.45 MB)
3 -Implementing Methods of Word2Vec.mp4 (6.93 MB)
4 -Continuous Bag of Words ( CBOW ).mp4 (21.36 MB)
5 -Project01 Implementing CBOW Part-01.mp4 (86.39 MB)
6 -Project01 Implementing CBOW Part-02.mp4 (103.19 MB)
7 -Project01 Implementing CBOW Part-03.mp4 (63.19 MB)
8 -Project02 Implementing CBOW using Large Corpus.mp4 (55.8 MB)
9 -Pretrained Word2Vec.mp4 (28.66 MB)
1 -Introduction of the section.mp4 (11.38 MB)
3 -Project02 Pretrained GloVe.mp4 (80.86 MB)
1 -Introduction of the section.mp4 (22.24 MB)
1 -Introduction of the section.mp4 (11.03 MB)
2 -Markov Model and State Transition Matrix.mp4 (45.02 MB)
3 -Project01 Text Generation by State Transition Matrix.mp4 (96.22 MB)
4 -First Order Markov Model for Text Generation.mp4 (58.39 MB)
5 -Project02 Text Generation by First Order Markov Model.mp4 (180.08 MB)
6 -Second Order Markov Model.mp4 (21.19 MB)
7 -Project03 Text Generation by Second Order Markov Model.mp4 (78.65 MB)
8 -Project04 Text Generation by Second Order Markov Model using Large Corpus.mp4 (70.3 MB)
9 -Project05 Text Generation by Third Order Markov Model.mp4 (58.46 MB)
1 -Introduction of the section.mp4 (6.97 MB)
10 -Project02 Time Series Prediction by LSTM.mp4 (83 MB)
11 -MNIST Classification by LSTM.mp4 (8.83 MB)
12 -Project03 MNIST Classification Part01.mp4 (35.6 MB)
13 -Project03 MNIST Classification Part02.mp4 (21.19 MB)
14 -Text Classification.mp4 (24.11 MB)
15 -Project04 Text Preprocessing.mp4 (44.42 MB)
16 -Project05 Text Classification by LSTM.mp4 (91.46 MB)
2 -Need of RNN.mp4 (15.46 MB)
3 -Sequential Data.mp4 (14.68 MB)
4 -ANN to RNN.mp4 (27.37 MB)
5 -Back Propagation Through Time.mp4 (68.15 MB)
6 -Long Short Term Memory ( LSTM ).mp4 (18.82 MB)
7 -LSTM Gates.mp4 (48.09 MB)
8 -Concept of Batch size, Sequence length and Feature dimension.mp4 (59.15 MB)
9 -Project01 LSTM Shapes.mp4 (164.05 MB)
1 -Introduction of the section.mp4 (11.34 MB)
2 -Implementing Seq2Seq Network and Teacher Forcing.mp4 (54.77 MB)
3 -Project01 Text Generation by Seq2Seq Network.mp4 (119.28 MB)
4 -Project02 Machine Translation ( Language Translation ) by Seq2Seq Network.mp4 (120.1 MB)
1 -Introduction of the section.mp4 (8.49 MB)
2 -Mounting the drive and reading Dataset.mp4 (81.04 MB)
3 -Reading and displaying images.mp4 (50.14 MB)
4 -Reading More Datasets.mp4 (28.89 MB)
5 -Uploading Course Material to Google drive.mp4 (16.87 MB)
1 -Introduction of the section.mp4 (28.91 MB)
2 -Project01 Sentiment Analysis.mp4 (115.26 MB)
3 -Project02 Text Generation.mp4 (78.05 MB)
4 -Project03 Masked Language Modeling.mp4 (81.99 MB)
5 -Project04 Text Summarization.mp4 (100.94 MB)
6 -Project05 Machine Translation.mp4 (78.29 MB)
7 -Project06 Question Answering.mp4 (98.09 MB)
1 -Fundamental Building Blocks of Transformer.mp4 (32.64 MB)
2 -Encoder and Decoder.mp4 (47.82 MB)
3 -Positional Encoding.mp4 (29.02 MB)
4 -Attention Mechanism.mp4 (58.17 MB)
1 -Introduction of the section.mp4 (8.77 MB)
2 -Project01 Model and Tokenization.mp4 (128.18 MB)
3 -Project02 Fine Tuning Transformer for Sentiment Analysis.mp4 (137.08 MB)
4 -Project03 Fine Tuning Transformer on Custom Dataset.mp4 (131 MB)
1 -Introduction of the section.mp4 (5 MB)
1 -Introduction of the section.mp4 (6.26 MB)
2 -Working of Bidirectional LSTM.mp4 (14.06 MB)
3 -Project01 Shapes of Bidirectional LSTM.mp4 (68.24 MB)
4 -Project02 Bidirectional LSTM for MNIST dataset.mp4 (52.82 MB)
5 -Dual Bidirectional LSTM.mp4 (12.13 MB)
6 -Project03 Dual Bidirectional LSTM for MNIST dataset.mp4 (88 MB)
1 -Introduction of the section.mp4 (11.19 MB)
2 -Project01 Shapes of Encoder.mp4 (75.24 MB)
3 -Project02 Time Series Classification.mp4 (122.99 MB)
4 -Project03 Time Series Transformer Shapes.mp4 (34.25 MB)
5 -Project04 Time Series Reconstruction by Time Series Transformer.mp4 (99.04 MB)
1 -Introduction of the section.mp4 (9.08 MB)
10 -Plotting and Visualization Part03.mp4 (84.51 MB)
11 -Plotting and Visualization Part04.mp4 (58.39 MB)
12 -Lists in Python.mp4 (96.04 MB)
13 -For Loops Part01.mp4 (94.45 MB)
14 -For Loops Part02.mp4 (100.14 MB)
15 -While Loop.mp4 (59.77 MB)
16 -Strings in Python.mp4 (70.79 MB)
17 -Print Formatting with Strings.mp4 (18.89 MB)
18 -Dictionaries Part01.mp4 (39.51 MB)
19 -Dictionaries Part02.mp4 (41.34 MB)
2 -Arithmetic with Python.mp4 (49.18 MB)
20 -Seaborn part01.mp4 (55.52 MB)
21 -Seaborn part02.mp4 (40.61 MB)
22 -Seaborn part03.mp4 (46.23 MB)
23 -Pandas Part01.mp4 (41.91 MB)
24 -Pandas Part02.mp4 (33.15 MB)
25 -Pandas Part03.mp4 (65.26 MB)
26 -Pandas Part04.mp4 (48.2 MB)
27 -Functions in Python Part01.mp4 (40.72 MB)
28 -Functions in Python Part02.mp4 (37.33 MB)
29 -Classes in Python.mp4 (89.67 MB)
3 -Comparison and Logical Operations.mp4 (27.33 MB)
30 -Tuples.mp4 (38.67 MB)
31 -Lambda Function.mp4 (46.4 MB)
32 -Map Function.mp4 (45.42 MB)
33 -Reduce Function.mp4 (27.62 MB)
34 -Filter function.mp4 (26.77 MB)
35 -zip function.mp4 (48.12 MB)
36 -join function.mp4 (22.75 MB)
4 -Conditional Statements.mp4 (40.31 MB)
5 -NumPy Arrays Part01.mp4 (65.53 MB)
6 -NumPy Arrays Part02.mp4 (75.49 MB)
7 -NumPy Arrays Part03.mp4 (62.04 MB)
8 -Plotting and Visualization Part01.mp4 (104.06 MB)
9 -Plotting and Visualization Part02.mp4 (132.26 MB)
1 -Introduction to NLP.mp4 (23.95 MB)
2 -NLP History.mp4 (18.28 MB)
3 -Applications of NLP.mp4 (44.17 MB)
4 -Vocabulary and Corpus.mp4 (11.09 MB)
1 -Introduction of the section.mp4 (7.36 MB)
2 -Tokenization and Challenges.mp4 (24.57 MB)
3 -Types of Tokenization.mp4 (21.45 MB)
4 -Project01 Tokenization with Python.mp4 (58.27 MB)
5 -Project02 Tokenization with NLTK.mp4 (36.84 MB)
6 -Stemming, Lemmatization and Stopwords.mp4 (27.21 MB)
7 -Stemming and Lemmatization with NLTK.mp4 (90.41 MB)
1 -Introduction of the section.mp4 (5.59 MB)
2 -Word to Index Mapping.mp4 (12.05 MB)
3 -Word to Index Mapping with Python.mp4 (59.94 MB)
4 -Bag of Words.mp4 (40.56 MB)
5 -Count Vectorizer.mp4 (23.83 MB)
6 -Count Vectorizer with Python.mp4 (85.24 MB)
7 -Machine Learning with Count Vectorizer.mp4 (95.34 MB)
8 -TF-IDF Vectorizer.mp4 (57.37 MB)
9 -TF-IDF Vectorizer in Python.mp4 (56.65 MB)
1 -Introduction of the section.mp4 (8.82 MB)
1 -Introduction of the section.mp4 (14.6 MB)
10 -Numerical Example on KNN.mp4 (28.05 MB)
11 -Project02 Sentiment Analysis With KNN.mp4 (61.68 MB)
12 -Pre-trained Sentiment Analysis Model.mp4 (27.85 MB)
2 -Basic Concept of Logistic Regression.mp4 (35.58 MB)
3 -Limitations of Regression.mp4 (29.39 MB)
4 -Transforming Linear Regression into Logistic Regression.mp4 (27.65 MB)
5 -Model Evaluation.mp4 (35.21 MB)
6 -Accuracy-Precision-Recall-F1 score.mp4 (67.9 MB)
7 -Project01 Sentiment Analysis by Logistic Regression.mp4 (150.86 MB)
8 -Intuition behind K-Nearest Neighbor ( KNN ).mp4 (15.4 MB)
9 -KNN Algorithm.mp4 (13.12 MB)
1 -Introduction of the section.mp4 (9.97 MB)
10 -Hard and Soft Margin Classifier.mp4 (15.63 MB)
11 -Decision rule for SVM.mp4 (17.2 MB)
12 -Kernel trick in SVM.mp4 (28.71 MB)
13 -Spam detection with SVM.mp4 (61.8 MB)
2 -Fundamentals of Probability.mp4 (54.96 MB)
3 -Conditional Probability and Bayes Theorem.mp4 (35.25 MB)
4 -Numerical on Bayes Theorem.mp4 (18.94 MB)
5 -Naive Bayes Classification.mp4 (33.98 MB)
6 -Comparing Naive Bayes Classification with Logistic Regression.mp4 (18.67 MB)
7 -Project01 Spam detection with Naive Bayes Classifier.mp4 (108.26 MB)
8 -Fundamentals of Support Vector Machine ( SVM ).mp4 (23.52 MB)
9 -Mathematics of SVM.mp4 (47.49 MB)
1 -Introduction of the section.mp4 (4.44 MB)
2 -Data Distribution in Statistics.mp4 (26.75 MB)
3 -Dirichlet Distribution.mp4 (33.24 MB)
4 -Applications of Dirichlet Distribution.mp4 (34.7 MB)]
Screenshot
[Image: VtV7GDhB_o.jpg]