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1,082 Bewertungen
263 Bewertungen

Über den Kurs

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...

Top-Bewertungen

MS
28. März 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!

GW
18. Feb. 2019

Really excellent. Very practical advice from top competitors. This specialization is much more information-dense than most machine learning MOOCs. You really get your money's worth.

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126 - 150 von 261 Bewertungen für How to Win a Data Science Competition: Learn from Top Kagglers

von James T

7. Mai 2018

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

von CINTHYA G C G

23. Juli 2020

Es un curso retante, que te permite reforzar y evaluar tus conocimientos en ML

von Mostafa M M

7. Jan. 2019

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

von Eric S

15. Okt. 2020

Lots of important insights. The final project was a great learning experience.

von Wesley A B J

16. März 2019

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

von Jbene M

20. Mai 2018

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

von Leonid G

26. März 2018

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

von Ramil G

25. März 2019

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

von Andrés V

19. Apr. 2021

Intense, detailed approach to sophisticated techniques. Recommended.

von CARLOS A R R

22. Nov. 2020

Really good course, some hard for the new lerners but really well

von Thamalu P

31. Aug. 2020

A very good course focusing practical stuff on model enhancement.

von Resve S

27. Juli 2018

Highly recommended for those wanting to be an advanced Kaggler!

von Angel D

30. Sep. 2019

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

von Aldo D

6. Apr. 2020

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

von Adithya N

18. Nov. 2019

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

von Lionel C

18. Feb. 2018

Awesome, Excellent.

It gives many tricks for a data scientist.

von abensaid

19. Mai 2019

very good courses makes me learn a lot practical examples

von Tin T Y

3. Apr. 2018

Awesome course. Learn things through hands-on assignment

von David A

24. Mai 2019

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

von Anatoly B

12. März 2018

Great course, finally an advanced data science track!

von Prashanth T

26. Okt. 2018

By far the most useful course i have ever taken! :)

von Andrei R

20. Mai 2020

Very practical course on applied machine learning.

von 강선구

12. Aug. 2019

This course is very helpful. Thank you to lectures

von CARLOS S G O

19. Juli 2020

It's a really good course, I learned many things.

von Debasis U

1. Aug. 2019

Amazing course! The lectures are great! Thank You