Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP Training Course
This course is intended for developers and data scientists who want to understand and implement artificial intelligence in their applications. Special focus is placed on data analytics, distributed AI, and natural language processing.
Course Outline
- Distributed data under big data
- Data mining method (training single machine + distributed prediction: traditional machine learning algorithm + Mapreduce distributed prediction,)
- Apache Spark MLlib
- Recommendations and targeted advertising:
- The natural language part
- Text clustering, text classification (labeling), synonyms
- User profile restoration, tag system
- Recommendation Algorithm Strategy
- Lift between classes, lift within classes, how to be precise
- How to build a closed loop for recommendation algorithms
- Logistic regression, RankingSVM,
- Feature recognition: (deep learning and automatic feature recognition of graphics)
- Natural Language
- Chinese word segmentation
- Topic Model (Text Clustering)
- Text Classification
- Extract keywords
- Semantic parser, word2vec to word vector
- RNN Long short-term memory (TSTM) Architecture
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Testimonials (1)
This is one of the best hands-on with exercises programming courses I have ever taken.
Laura Kahn
Course - Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
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