KSE MBAI Course: Natural Language Processing

Oleksandr Korobov

Oleksandr Korobov
AI Consultant, Software Engineer, founder AI-labs

April 24-26
KSE Business Education

Dmitrovskaya St. 92-94

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Description:

This course provides an overview of artificial intelligence and machine learning techniques for natural language processing. We will go through things like spell checking, syntax parsing, sentiment analysis, text classification, elements of natural language understanding, chatbots, text generating approaches. We will discuss the new cutting edge of technology types of language models.

Learning outcomes:

Students will know basic tools and techniques relevant to modern Natural Language Processing including corresponding machine learning background and programming tools.

Exams & certification:
After the successful completion of the course, the participants will get a certificate.

Speaker

Oleksandr Korobov

AI Consultant, Software Engineer, founder AI-labs

Oleksandr has a big experience in Software Engineering and Artificial Intelligence, including Natural Language Processing, and Machine Learning. Currently, he is a co-founder and a team member at AI-labs, Kyiv, Ukraine. Practices application of modern AI and Machine Learning approaches.

Education: Donbas State Mechanical Engineering Academy, Master’s degree in Dynamic Systems and Computer Science.

Expertise: Deep learning, Computer Vision, Machine Learning, Data Analysis, and Data Visualization.

Course outline:

Course outline:

1.Introduction: Natural Language Processing Goals and Problems. Initial overview.
NLP Goals, an overview of NLP problems and ways to solve them. Familiarizing with basic tools and
coding techniques essential for natural language analysis.

2. Machine Learning, Artificial Intelligence and algorithms overview for NLP.
NLP Goals, an overview of NLP problems and ways to solve them. Familiarizing with basic tools and
coding techniques essential for natural language analysis. Comparison of classic algorithms with cutting edge of technology neural network-based recent achievements.

3. Machine Learning, Artificial Intelligence and algorithms overview for NLP in a historical perspective.

AI Winters, Bayesian Methods, Support Vector Machines, Quality Performance plato in different epochs.

4. Programming tools for machine learning and natural language processing
Basics of Python, machine learning and NLP libs publicly available and intensively used.

5. Text Classification and Classic ML
Bayesian Methods, Support Vector Machines and text classification

6. Text Classification and Neural Networks
Bayesian Methods, Support Vector Machines and text classification

7. Overview of Machine Translation and Text Generating with neural networks
Sequence to sequence encoders (s2s) and their application for NLP

8. Language Models Comparison
Frequency-based and Deep models.

9. Natural Language Understanding, sense-based text vectorization
Word to Vector (w2w), Document to vector (d2v) and the idea of “embeddings”

10. NLP Business Tools
Chatbots, avatars, voice-related topics

11. Cutting Edge Of Technology recent publications and their impact
Transfer Learning, ElMO, BERT, OpenAI GPT, ULMfi

Registration

Price
24 000
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