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• NEW ADVANCES IN NATURAL LANGUAGE PROCESSING
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• 12 OPEN SOURCE TOOLS FOR NATURAL LANGUAGE PROCESSING
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• MORE-EFFICIENT “KERNEL METHODS” DRAMATICALLY REDUCE TRAINING TIME FOR NATURAL-LANGUAGE-UNDERSTANDING SYSTEMS
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• AI BLUEPRINTS: IMPLEMENTING CONTENT-BASED RECOMMENDATIONS USING PYTHON
  Jan 27

• NLP WITH A FASHION TWIST: ZALANDO’S NATURAL LANGUAGE PROCESSING FRAMEWORK
  Jan 21

• HUMANIZING CUSTOMER COMPLAINTS USING NLP ALGORITHMS
  Nov 27

• INTEL AI LAB OPEN-SOURCES LIBRARY FOR DEEP LEARNING-DRIVEN NLP
  May 24

• INTRODUCING STATE OF THE ART TEXT CLASSIFICATION WITH UNIVERSAL LANGUAGE MODELS
  May 15

• MACHINE LEARNING FOR TEXT CLASSIFICATION USING SPACY IN PYTHON
  May 14

• ALTEREGO: INTERFACING WITH DEVICES THROUGH SILENT SPEECH
  Apr 9

• CS224N: NATURAL LANGUAGE PROCESSING WITH DEEP LEARNING
  Apr 4

• BAIDU SHOWS OFF ITS INSTANT POCKET TRANSLATOR
  Mar 28

• USING AI TO MATCH HUMAN PERFORMANCE IN TRANSLATING NEWS FROM CHINESE TO ENGLISH
  Mar 15

• SEQUENCE TAGGING WITH TENSORFLOW
  Mar 14

• BUILDING A NEXT WORD PREDICTOR IN TENSORFLOW
  Mar 5

• UNDERSTANDING WORD VECTORS IN NLP
  Mar 3