Difference between revisions of "Class"
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* [http://en.wikipedia.org/wiki/Natural-language_processing Natural Language Processing] | * [http://en.wikipedia.org/wiki/Natural-language_processing Natural Language Processing] | ||
* [http://en.wikipedia.org/wiki/Sentiment_analysis Sentiment Analysis] | * [http://en.wikipedia.org/wiki/Sentiment_analysis Sentiment Analysis] | ||
| + | |||
| + | = Deep Autoencoders for Anomaly Detection = | ||
| + | |||
| + | Variable Auencoders | ||
| + | |||
| + | * clustering - latent layers may tell you what number of clusters | ||
| + | * anomaly detection | ||
| + | |||
| + | https://courses.nvidia.com/courses/course-v1:DLI+L-FI-06+V1/info | ||
| + | |||
| + | PCA or TSenee | ||
| + | |||
| + | Mean inversion | ||
| + | Statistical Arbitrage | ||
| + | arbitrage - monies, stocks (price is better than it should be - fair market value) how right, or how rich? | ||
| + | |||
| + | Autoecoder learn the fair market value, then feed in current value | ||
Revision as of 14:25, 23 October 2018
https://courses.nvidia.com/dashboard
Linguistic Concepts
- conference - anaphors
- gang of four design
- null subject
- recursion
Contents
Word Embeddings
- HMMS, CRF, PGMs
- CBoW -Bag of Words / ngrams - feature per word/n items
- 1-hot Sparse input - create a vector the size of the entire vocabulary
- Stop Words
- TF-IDF
Word2Vec
Skip-Gram
- Firth 1957 Distributional Hypothess
- Word Cloud
Text Classification
Text/Machine Translation (MNT)
Financial News
Yuval
Tools:
- Glove
- dot product
- FastText
- Skipgram
- Continuous bag of words
Multi-channel LSTM Network Keras wih TensorFlow Utilize the GloVe and FastText Skipgram pretrained embeddings, allows he underlying network to access larger feature space to build complex features on top of.
Can use utilize combinations of various corpus and embedding methods for better performance
Bidirectional LSTM network is used o encode sequential information on the embedding layers.
Dense layer to project fnal output classification
Use embedding... embeddings = transfer learning
? CNN vs BI-LSTM (RNN) this approach, BI-LSTM does not need a lot of data
Attention mechanism -- translate ... you can look back
... not a fixed vector size
- GloVe
- Fasttext
- News articles per day
- News data source
- Word embeddings
- Natural Language Processing
- Sentiment Analysis
Deep Autoencoders for Anomaly Detection
Variable Auencoders
- clustering - latent layers may tell you what number of clusters
- anomaly detection
https://courses.nvidia.com/courses/course-v1:DLI+L-FI-06+V1/info
PCA or TSenee
Mean inversion Statistical Arbitrage arbitrage - monies, stocks (price is better than it should be - fair market value) how right, or how rich?
Autoecoder learn the fair market value, then feed in current value
