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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

964 calificaciones
226 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 224 revisiones para How to Win a Data Science Competition: Learn from Top Kagglers

por Margarita C

Nov 07, 2019

This course is awesome. The more effort I invested in it - the more results I got, and I feel like I haven't reached the limit. The course is very thought-out, the tests and programming assignments are great, teachers are inspiring. I enjoyed every part of it!

por Igor B

Jan 27, 2019

This course requires much time, but gives hardcore experience in practical data science and machine learning. The final project, which is a proving ground for the acquired skills, is both an interesting competition to participate in and a real-world-task.

por Arnaud R

Mar 17, 2018

This course is a gold mine of knowledge and tricks for anyone working with the data science toolkit. It requires good prior knowledge of the different algorithm used and Python fluency. The course is demanding but you will get out of it so much stronger.

por Diego T B

Nov 07, 2019

This is an awesome course! I really learned a lot from this top kagglers. I just have one recommendation. I think some sessions were very though and difficult to catch: the data leakage part and the Kappa metric. Try to make this even much easier.

por Yotam S

Oct 26, 2019

Amazing course. Teaches the theoretical aspects of ML in within a practical point of view. Enables use to improve your models by understanding the framework much better. Not recommended as first ML course, but definitely as an advanced one.

por Holger P

Nov 19, 2017

This course is amazing. Taught by experts in the field with a proven track record of outstanding performance in Kaggle competitions. They teach how to fine tune ML models to achieve better performance. My choice for best course on Coursera!

por Amit K S

Jan 20, 2019

This is so good. Three reasons (1) Helps me revisit the concepts that I learnt in the machine learning course. (2) Helps me to deal with my FOMO (3) I would feel most confident to go for my Data Science or Data Engineering interviews.

por ashesh g m

Jun 10, 2019

It was one of the best courses which I've done on coursera. Here, it was all practical and essential knowledge which was taught. Mentors were amazing and inspiring. A must do for any data scientist or aspiring data scientist.

por Alex

Feb 25, 2018

It's tough to pass this course tasks and the course itself not 100% polished, but it makes it very interesting in the practical aspect - I learned more. Also, I believe lectors gave us a lot of very helpful material.

por Olaf W

May 10, 2018

Really liked the class. Didn't expect to learn a whole lot of new things, but they have some great tips and tricks here and there that I hadn't come across yet which made it worthwhile.

The content is well structured.

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 venkata y

May 04, 2020

the best course i did on coursera. it was amazing to learn from the winners of previous competitions.

definitely not from starters. you need to decent background. it is climbing a hill from the get-go

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 Алексей Ш

May 29, 2020

Спасибо авторам курса! На мой взгляд им удалось пройти по тонкой грани между достаточностью и избыточностью информации. Все информация и дополнительные ссылки - очень полезны. Отличный курс!

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 :)