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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

812 calificaciones
172 revisiones

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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:

Principales revisiones


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!


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.

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51 - 75 de 170 revisiones para How to Win a Data Science Competition: Learn from Top Kagglers

por Chris M

Jul 24, 2019

This was one of the better online courses I've taken in Machine Learning. There is so much content in this course, and I've learned a lot from the exercises and working on the Predicting Future Sales competition.

por Hulot

Feb 17, 2019

A must for every data scientist, the courses are amazing and you learn a lot a tips.

If you have just started data science, you’ll be able to follow the course but you may not understand all the underlying ideas

por Joseph B

Apr 18, 2019

Very nice course and final project is actually challenging and a great learning experience when learner attempts to do it completely on their own without reading forums or looking at examples on Kaggle.

por robert

Jan 02, 2019

Challenging in a fun way, puts things I've learnt before in a different perspective. Overall very practical knowledge with lots of use-cases and not much theory. it's like an awesome lab in grad school.

por Marat S

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!

por P C T

Mar 16, 2020

The course is really excellent way of teaching the exploratory data analysis and ensembling concepts, i hope i will start a new life with the knowledge gained by this course

por Charles-Antoine d T

Aug 05, 2018

Clear and challenging at the same time, perfect!

I did quite a few courses on Coursera now (Specialisation in Data Science and Deep Learning and this one is clearly in my top

por Darya L

Aug 20, 2018

The course is very interesting. All topics are clearly explained. Helped me a lot with data preprocessing, metrics, hyperparameters optimization and stacking. Thanks a lot!

por nicole s

Apr 17, 2018

Finally an advanced and comprehensive course in data science! Straight to the point with an extremely useful guidance on how to apply and analyse predictive models!


Mar 11, 2019

Great course.

Even if some lessons may seem too theorical, it all comes together during the final project which pushes you to look back and apply what you learned.

por Anna N

Mar 07, 2018

Very interesting course, it really covers material you will find nowhere! It is very practical, interesting topics and assignments!

I like this course very much.

por Quan T

Feb 18, 2018

This is a good course. There are lots of useful tips and tricks to get more predictive power from data and model. I feel more confident in competing on Kaggle

por Ilya E

Apr 27, 2018

Very practical course for those who are already good at ML. Not academical, not beginner-level. Once you get used to Russian accent it goes really well :)

por Saulo M d M

Nov 04, 2019

Great course! You will learn very advanced modeling techniques that are not only useful for data competitions but also real machine learning applications.

por Anthony I S

Dec 31, 2017

Great course not just for competing in Kaggle, but also for giving a deeper understanding towards other things in machine learning besides the algorithms

por jagannadha R b

Oct 17, 2019

One of the best course with the top kagglers sharing their experience of solving the most complex data science problems. ! Thanks to Courseera !


por Diego S d B

Dec 19, 2019

Excellent. One of the best courses I've ever done! I hope the other courses on the specialization are as awesome as this one. Unique content!

por Mukesh R

Jul 15, 2019

A very well made course and it has lots of useful information related to field of data science. Thank you for making it available to us.

por Nikolay C

Mar 25, 2019

Excellent course! Previously I had a small experience in Kaggle competitions, but this course really charged me with new superskills! :)

por Regi M

Aug 14, 2018

This course stands out as the instructors provide details of all concepts they discuss. It is also supported by numerical exercises.

por ahmed a

Aug 27, 2018

Very interesting course that gives you a cutting edge in public competitions. Many ideas that rarely seen in class rooms.

por Vishal B

Jan 25, 2019

Really great course, with so great insights! I really enjoyed the talks on feature engineering and ensemble methods!

por Oleg O

Dec 09, 2018

Very handy course, except I wasn't motivated enough to do home assignments. However, I gained a lot of new concepts

por Evgeny K

Oct 18, 2018

Learned many interesting moments in competitive ML! The course is systematic and structured very good, recommend!

por Murat Ö

May 21, 2019

It is a well prepared course which includes lots of tips and trick and theoretical background to be successful.