Index
A
Abstractive summarization
AI life cycle
business context
business problems
data cleaning and preprocessing
data collection and understanding
data science problems
deployment/productionization and model maintenance
exploratory data analysis
feature engineering and selection
model building, tuning and selection
model testing and validation
prediction and insights
scenarios
solution approach/architecture design
Amazon Web Services (AWS)
Artificial intelligence (AI)
concept
paradigm
Artificial neural network (ANN)
Attention mechanism
Autoencoders
Automated reporting
AutoNLP
Autosuggestion
B
Backpropagation
BART
Bidirectional encoder representations from transformers (BERT)
Bidirectional LSTM
Business context
C
Capsule networks
Chatbots
applications
context-based pretrained model ...
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