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[ CourseWikia.com ] Deep Learning with Python and Keras - Build a Model For Sentiment Analysis
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[ CourseWikia.com ] Deep Learning with Python and Keras - Build a Model For Sentiment Analysis
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c52b22bae9420e72918ea83c78d3cc68fdfa2ec7
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收录时间:
2024-09-29
最近下载:
2025-05-31
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文件列表
~Get Your Files Here !/04 - 3. Chapter Name/10 - Training ADNN using embeddings.mp4
15.4 MB
~Get Your Files Here !/04 - 3. Chapter Name/03 - Representing text using count vectorization.mp4
14.9 MB
~Get Your Files Here !/03 - 2. Chapter Name/04 - Cleaning and preprocessing text.mp4
13.5 MB
~Get Your Files Here !/04 - 3. Chapter Name/07 - Representing text using TFIDF vectorization.mp4
9.5 MB
~Get Your Files Here !/02 - 1. Chapter Name/02 - Word vector encodings and word embeddings.mp4
9.4 MB
~Get Your Files Here !/04 - 3. Chapter Name/04 - Configuring the dense neural network (DNN).mp4
9.4 MB
~Get Your Files Here !/02 - 1. Chapter Name/04 - Approaches and challenges in sentiment analysis.mp4
9.0 MB
~Get Your Files Here !/05 - 4. Chapter Name/02 - Long memory cells.mp4
8.9 MB
~Get Your Files Here !/05 - 4. Chapter Name/04 - Training a recurrent neural network.mp4
8.1 MB
~Get Your Files Here !/04 - 3. Chapter Name/08 - Training and evaluating the model.mp4
8.0 MB
~Get Your Files Here !/03 - 2. Chapter Name/02 - Importing Python modules and loading data.mp4
7.8 MB
~Get Your Files Here !/04 - 3. Chapter Name/01 - Feed-forward neural networks.mp4
7.7 MB
~Get Your Files Here !/03 - 2. Chapter Name/03 - Analyzing word lengths across sentiment categories.mp4
7.6 MB
~Get Your Files Here !/01 - Introduction/01 - An overview of sentiment analysis.mp4
7.6 MB
~Get Your Files Here !/05 - 4. Chapter Name/05 - Training an LSTM network.mp4
7.3 MB
~Get Your Files Here !/04 - 3. Chapter Name/02 - Splitting data into training test and validation sets.mp4
7.3 MB
~Get Your Files Here !/04 - 3. Chapter Name/05 - Training and evaluating the DNN.mp4
6.9 MB
~Get Your Files Here !/05 - 4. Chapter Name/06 - Serializing a model to disk and loading the model.mp4
6.8 MB
~Get Your Files Here !/03 - 2. Chapter Name/01 - Getting set up with Google Colab.mp4
6.7 MB
~Get Your Files Here !/05 - 4. Chapter Name/01 - Recurrent neural networks.mp4
6.5 MB
~Get Your Files Here !/05 - 4. Chapter Name/03 - The LSTM and GRU cells.mp4
5.8 MB
~Get Your Files Here !/02 - 1. Chapter Name/03 - Types of sentiment analysis.mp4
5.7 MB
~Get Your Files Here !/04 - 3. Chapter Name/09 - Representing text using integer sequences.mp4
5.4 MB
~Get Your Files Here !/04 - 3. Chapter Name/06 - Configuring the count vectorizer as a model layer.mp4
5.3 MB
~Get Your Files Here !/03 - 2. Chapter Name/05 - Visualizing text using word clouds.mp4
5.0 MB
~Get Your Files Here !/02 - 1. Chapter Name/01 - Preprocessing text for sentiment analysis.mp4
4.0 MB
~Get Your Files Here !/Ex_Files_Deep_Learning_Python_Keras/Exercise Files/final_code/dataset/Tweets.csv
3.5 MB
~Get Your Files Here !/06 - Conclusion/01 - Summary and next steps.mp4
2.9 MB
~Get Your Files Here !/Ex_Files_Deep_Learning_Python_Keras/Exercise Files/final_code/demo_01_SentimentAnalysisUsingNeuralNetworksWithKeras.ipynb
1.9 MB
~Get Your Files Here !/01 - Introduction/02 - Prerequisites.mp4
1.4 MB
~Get Your Files Here !/04 - 3. Chapter Name/03 - Representing text using count vectorization.srt
13.7 kB
~Get Your Files Here !/04 - 3. Chapter Name/10 - Training ADNN using embeddings.srt
12.7 kB
~Get Your Files Here !/02 - 1. Chapter Name/02 - Word vector encodings and word embeddings.srt
11.1 kB
~Get Your Files Here !/02 - 1. Chapter Name/04 - Approaches and challenges in sentiment analysis.srt
11.0 kB
~Get Your Files Here !/03 - 2. Chapter Name/04 - Cleaning and preprocessing text.srt
10.9 kB
~Get Your Files Here !/04 - 3. Chapter Name/04 - Configuring the dense neural network (DNN).srt
9.5 kB
~Get Your Files Here !/05 - 4. Chapter Name/02 - Long memory cells.srt
9.2 kB
~Get Your Files Here !/01 - Introduction/01 - An overview of sentiment analysis.srt
8.8 kB
~Get Your Files Here !/04 - 3. Chapter Name/07 - Representing text using TFIDF vectorization.srt
8.6 kB
~Get Your Files Here !/04 - 3. Chapter Name/01 - Feed-forward neural networks.srt
8.1 kB
~Get Your Files Here !/03 - 2. Chapter Name/03 - Analyzing word lengths across sentiment categories.srt
7.8 kB
~Get Your Files Here !/03 - 2. Chapter Name/02 - Importing Python modules and loading data.srt
7.4 kB
~Get Your Files Here !/05 - 4. Chapter Name/01 - Recurrent neural networks.srt
7.1 kB
~Get Your Files Here !/04 - 3. Chapter Name/02 - Splitting data into training test and validation sets.srt
6.9 kB
~Get Your Files Here !/03 - 2. Chapter Name/01 - Getting set up with Google Colab.srt
6.8 kB
~Get Your Files Here !/05 - 4. Chapter Name/03 - The LSTM and GRU cells.srt
6.5 kB
~Get Your Files Here !/02 - 1. Chapter Name/03 - Types of sentiment analysis.srt
6.5 kB
~Get Your Files Here !/05 - 4. Chapter Name/04 - Training a recurrent neural network.srt
6.4 kB
~Get Your Files Here !/05 - 4. Chapter Name/06 - Serializing a model to disk and loading the model.srt
6.3 kB
~Get Your Files Here !/04 - 3. Chapter Name/05 - Training and evaluating the DNN.srt
5.6 kB
~Get Your Files Here !/04 - 3. Chapter Name/08 - Training and evaluating the model.srt
5.6 kB
~Get Your Files Here !/05 - 4. Chapter Name/05 - Training an LSTM network.srt
5.4 kB
~Get Your Files Here !/02 - 1. Chapter Name/01 - Preprocessing text for sentiment analysis.srt
5.2 kB
~Get Your Files Here !/04 - 3. Chapter Name/09 - Representing text using integer sequences.srt
5.2 kB
~Get Your Files Here !/04 - 3. Chapter Name/06 - Configuring the count vectorizer as a model layer.srt
4.6 kB
~Get Your Files Here !/06 - Conclusion/01 - Summary and next steps.srt
3.8 kB
~Get Your Files Here !/03 - 2. Chapter Name/05 - Visualizing text using word clouds.srt
3.0 kB
~Get Your Files Here !/01 - Introduction/02 - Prerequisites.srt
1.9 kB
~Get Your Files Here !/Bonus Resources.txt
386 Bytes
Get Bonus Downloads Here.url
181 Bytes
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