Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP 교육 과정

  1. 빅 데이터 Training
  2. Apache Spark Training
  3. Apache Spark MLlib Training
  4. Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP 교육 과정

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

  1. Distribution big data
    1. Data mining methods (training single systems + distributed prediction: traditional machine learning algorithms + Mapreduce distributed prediction)
    2. Apache Spark MLlib
  2. 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
  3. Logical regression, RankingSVM,
  4. Feature recognition (deep learning and automatic feature recognition for graphics)
  5. 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

회원 평가

★★★★★
★★★★★

Related Categories

Related Courses

Artificial Intelligence OverviewBuilding Chatbots in PythonDeep Learning for NLP (Natural Language Processing)Python for Natural Language GenerationNatural Language ProcessingNLP: Natural Language Processing with ROpenNLP for Text Based Machine LearningPython: Machine Learning with TextNatural Language Processing with Deep Dive in Python and NLTKNatural Language Processing with PythonNatural Language Processing (NLP) with Python spaCyApache Spark MLlibText Summarization with PythonNatural Language Processing with TensorFlowNLP with Deeplearning4j

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