DS207BKK
Machine Learning in Applications for Text Mining
Faculty
Sergey Khoroshenkikh
Senior Software Engineer at Yandex
Course length
Duration
Total hours
Credits
Language
Course type
Fee for single course
Fee for degree students
Skills you’ll learn
Overview
Machine learning is a tool that helps to solve various problems which require prediction, pattern recognition, or classification. Without machine learning, entire industries and technologies (search engines, recommendation systems, or self-driving cars) wouldn't exist. Also, machine learning enables breakthroughs in traditional fields - physics, biology, and medicine, to name a few.
In this course, you will study various machine learning methods by solving a large number of practical tasks. We will consider both classic feature-based algorithms and modern approaches based on neural networks.
Learning highlights
- Which machine learning methods are frequently used in practical applications
- How to combine various machine learning algorithms to solve real-world problems
- What problems may arise when using machine learning and how to avoid them
Course outline
15 classes
Linear models in the wild
- Feature engineering for linear models.
- Typical use cases and applications.
- Optimization methods.
Decision trees. Gradient boosting.
- Induction of decision trees.
- Ensemble methods: Random Forest, Gradient Boosting.
- CatBoost.
Neural networks I
- Universal approximators.
- Backpropagation
- Optimization methods
- PyTorch
Neural networks II
- Regularization and training of deep neural networks.
- Convolutional neural networks.
- Recurrent neural networks
- Transformers
Self-supervised learning
- Word2Vec
- Triplet loss
- Generative models: autoencoders, language models
Machine learning models understanding
- Feature importance
- SHAP values
- Masking
- Embeddings
Pre-trained deep learning models
- Pre-trained deep learning models
Models stacking
- Stacking, blending, voting
- Time-dependent features
Learning to rank
- Problem statement
- Metrics and loss functions
- Algorithms
Recommender systems
- Problem statement
- Collaborative filtering
- Content-based approach
Case study: voice assistant
Case study: voice assistant
Case study: news aggregator
Case study: news aggregator
Case study: duplicate ads detection
Case study: duplicate ads detection
Machine learning systems architecture
A typical MLOps pipeline
Final projects session
Final projects session
Prerequisites
Strong programming background (Python)
Understanding of machine learning concepts and algorithms (at least an introductory Machine Learning course is required)
Solid knowledge of multivariate calculus and linear algebra
Methodology
The course is focused on practical machine learning methods and tools, yet providing a necessary theoretical and algorithmic background.
During the course, students will choose a machine learning problem, explore it and present the results of the research in the final session.
Also, sessions 1-10 will be followed by graded assignments.
Grading
Sergey Khoroshenkikh is a senior software engineer with eight years of experience in applied machine learning and data analysis. He graduated from the Moscow Institute of Physics and Technology in 2015. At Yandex, he has been working on large-scale machine learning solutions for web advertising as well as routing algorithms for Yandex Delivery.
Research/Academic Interests: Random graphs, complex networks
See full profileApply for this course
Machine Learning in Applications for Text Mining
by Sergey Khoroshenkikh
Total hours
45 Hours
Dates
Jan 09 - Jan 27, 2023
Fee for single course
€1500
Fee for degree students
€750
How to secure your spot
Complete the form below to kickstart your application
Schedule your Harbour.Space interview
If successful, get ready to join us on campus
FAQ
Will I receive a certificate after completion?
Yes. Upon completion of the course, you will receive a certificate signed by the director of the program your course belonged to.
Do I need a visa?
This depends on your case. Please check with the Spanish or Thai consulate in your country of residence about visa requirements. We will do our part to provide you with the necessary documents, such as the Certificate of Enrollment.
Can I get a discount?
Yes. The easiest way to enroll in a course at a discounted price is to register for multiple courses. Registering for multiple courses will reduce the cost per individual course. Please ask the Admissions Office for more information about the other kinds of discounts we offer and what you can do to receive one.