Chevron Left
Volver a How to Win a Data Science Competition: Learn from Top Kagglers

Opiniones y comentarios de aprendices correspondientes a How to Win a Data Science Competition: Learn from Top Kagglers por parte de National Research University Higher School of Economics

4.7
estrellas
817 calificaciones
174 revisiones

Acerca del Curso

If you want to break into competitive data science, then this course is for you! Participating in predictive modelling competitions can help you gain practical experience, improve and harness your data modelling skills in various domains such as credit, insurance, marketing, natural language processing, sales’ forecasting and computer vision to name a few. At the same time you get to do it in a competitive context against thousands of participants where each one tries to build the most predictive algorithm. Pushing each other to the limit can result in better performance and smaller prediction errors. Being able to achieve high ranks consistently can help you accelerate your career in data science. In this course, you will learn to analyse and solve competitively such predictive modelling tasks. When you finish this class, you will: - Understand how to solve predictive modelling competitions efficiently and learn which of the skills obtained can be applicable to real-world tasks. - Learn how to preprocess the data and generate new features from various sources such as text and images. - Be taught advanced feature engineering techniques like generating mean-encodings, using aggregated statistical measures or finding nearest neighbors as a means to improve your predictions. - Be able to form reliable cross validation methodologies that help you benchmark your solutions and avoid overfitting or underfitting when tested with unobserved (test) data. - Gain experience of analysing and interpreting the data. You will become aware of inconsistencies, high noise levels, errors and other data-related issues such as leakages and you will learn how to overcome them. - Acquire knowledge of different algorithms and learn how to efficiently tune their hyperparameters and achieve top performance. - Master the art of combining different machine learning models and learn how to ensemble. - Get exposed to past (winning) solutions and codes and learn how to read them. Disclaimer : This is not a machine learning course in the general sense. This course will teach you how to get high-rank solutions against thousands of competitors with focus on practical usage of machine learning methods rather than the theoretical underpinnings behind them. Prerequisites: - Python: work with DataFrames in pandas, plot figures in matplotlib, import and train models from scikit-learn, XGBoost, LightGBM. - Machine Learning: basic understanding of linear models, K-NN, random forest, gradient boosting and neural networks. Do you have technical problems? Write to us: coursera@hse.ru...

Principales revisiones

MS

Mar 29, 2018

Top Kagglers gently introduce one to Data Science Competitions. One will have a great chance to learn various tips and tricks and apply them in practice throughout the course. Highly recommended!

MM

Nov 10, 2017

This course is fantastic. It's chock full of practical information that is presented clearly and concisely. I would like to thank the team for sharing their knowledge so generously.

Filtrar por:

76 - 100 de 173 revisiones para How to Win a Data Science Competition: Learn from Top Kagglers

por S V

Jun 11, 2019

Strongly recommended. The course did not seem appealing at first, but it was challenging and I learned a lot.

por Pablo V I

Jun 01, 2018

Challenging and fun. Perfect course in order to learn advanced machine learning techniques for competitions.

por Sylvain D

Oct 06, 2019

One of my favorite courses, you learn a lot of extremely practical things !! Not so easy, need hard work.

por Karthikeyan S

Feb 22, 2018

Brilliant course. Thanks a ton for all the instructors. They are a real inspiration.

Regards - Karthik

por Thiru T N B

Aug 10, 2019

Excellent course! Brilliant to gain a strong understanding of applying machine learning principles.

por Frédéric G

Jun 11, 2019

Great ! I learned a lot with this course and a lot of things will be useful for my daily business

por Shanaya M

Oct 12, 2018

Very informative course. Aspiring data scientists could benefit greatly through this course.

por superfantastic

Nov 06, 2018

One of the Most Great course I have participate in . Thank you for all the instructors.

por Willian W

May 20, 2018

A very complete course, perfect to who wants to learn new techniques for data science.

por mar m

Aug 19, 2019

Multi-disciplinar course, a bit though but very useful and with a practical approach

por James T

May 07, 2018

Excellent and covers topics I've not seen in otherwise online courses. Great job!

por Mostafa M M

Jan 07, 2019

Really rich course with a lot of practical information, I learned a lot from it.

por Wesley A B J

Mar 16, 2019

Loving the course se far, ending 3rd week now. Very well explained conpets.

por jbene m

May 20, 2018

Really a Great Course, with a lot of informations summarized in short time.

por Leonid G

Mar 26, 2018

Really exciting and useful course! Plenty of desired information and tips.

por Ramil G

Mar 25, 2019

This course provides some unique knowledge you can't obtain anywhere else

por Resve S

Jul 27, 2018

Highly recommended for those wanting to be an advanced Kaggler!

por Angel D

Sep 30, 2019

Some top tips which are hard to find in other online resources

por Aldo D

Apr 06, 2020

one of the most awesome and interesting course i've ever seen

por Adithya N

Nov 18, 2019

Fantastic! It's the most intense course I've done on Coursera

por Lionel C

Feb 18, 2018

Awesome, Excellent.

It gives many tricks for a data scientist.

por abensaid

May 19, 2019

very good courses makes me learn a lot practical examples

por Tin T Y

Apr 03, 2018

Awesome course. Learn things through hands-on assignment

por David A

May 25, 2019

Learned a lot from this course. I highly recommend it.

por Anatoly B

Mar 12, 2018

Great course, finally an advanced data science track!