Course Code

aitech

Duration

21 hours (usually 3 days including breaks)

Overview

This course is aimed at developers and data scientists who wish to understand and implement AI within their applications. Special focus is given to Data Analysis, Distributed AI and NLP.

Course Outline

Distribution big data
1. Data mining methods (training single systems + distributed prediction: traditional machine learning algorithms + Mapreduce distributed prediction)
2. Apache Spark MLlib
Recommendations and Advertising:
1. Natural language
2. Text clustering, text categorization (labeling), synonyms
3. User profile restore, labeling system
4. Recommended algorithms
5. Insuring the accuracy of "lift" between and within categories
6. How to create closed loops for recommendation algorithms
Logical regression, RankingSVM,
Feature recognition (deep learning and automatic feature recognition for graphics)
Natural language
1. Chinese word segmentation
2. Theme model (text clustering)
3. Text classification
4. Extract keywords
5. Semantic analysis, semantic parser, word2vec (vector to word)
6. RNN long-term memory (TSTM) architecture