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1,081 Bewertungen
262 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:


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!

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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176 - 200 von 260 Bewertungen für How to Win a Data Science Competition: Learn from Top Kagglers

von なかむら

10. Juli 2020

programming assignment is good.

von Raheel H

6. Aug. 2020

A great learning experience.

von Graig L

13. Nov. 2020

Great course, very useful!

von Germán A R D

13. Okt. 2020

Excelente curso, exigente.

von JOHN F V O

11. Sep. 2020

Good and demanding curse

von Akshit J

28. Juli 2020

Really insightful course.

von Yingxin W

18. Apr. 2020

A lot of good materials

von Maniar T G

26. Sep. 2019

Amazing Course. Thanks!

von Renyi Z

29. Nov. 2020

Thanks. Learned a lot!

von Boris G A

22. Juni 2020

Hiper super course :D

von sagar s

29. Sep. 2018

Awesome. Worth it!.

von Ujjwal U

27. Jan. 2018

Exceptional course!

von Moti T

4. Jan. 2018

Interesting and fun

von Chiang y

26. Juli 2018

Excellent class!!!

von GUO S

23. Juli 2018

Like it very much!

von Evgeny V

13. März 2021

It was quite hard

von Mauricio D A

19. Nov. 2017

Very nice tricks!

von Alexis S

4. Feb. 2019

Very good course

von himanshu t

23. Jan. 2018

really great..!!


21. Juli 2018

awesome course

von Aditya S

1. Mai 2018

Amazing Course

von Anti L

6. Feb. 2021

Great course!

von Arif R

26. Aug. 2020

Excellent !!!

von Mike K

17. Jan. 2019

Отличный курс

von Ivan S

12. Jan. 2019

Great course!