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Avis et commentaires pour d'étudiants pour How to Win a Data Science Competition: Learn from Top Kagglers par Université HSE

4.7
étoiles
1,112 évaluations
274 avis

À propos du cours

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 online 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...

Meilleurs avis

MS
28 mars 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!

JD
20 déc. 2021

Very interesting course, touching on a lot of topics. It is on the hard side, especially the final project, but it is worth it. I would definitely recommend it to anyone interested in the topic.

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126 - 150 sur 273 Avis pour How to Win a Data Science Competition: Learn from Top Kagglers

par superfantastic

6 nov. 2018

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

par Willian W

20 mai 2018

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

par John F P

22 nov. 2020

Buen curso, se necesita definitivamente tener varias bases antes de hacer este curso.

par Atul S

11 mai 2020

Awesome course for those looking to enter in the domain of competitive data science.

par mar m

19 août 2019

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

par Nguyen V L

7 mai 2020

This course is very helpful for people who have a basic knowledge of Data Science.

par Denis R

5 mai 2020

Helps me to structure all already known information and learn a lot of new things

par James T

7 mai 2018

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

par CINTHYA G C G

23 juil. 2020

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

par Mostafa M M

7 janv. 2019

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

par Eric S

15 oct. 2020

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

par Wesley A B J

16 mars 2019

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

par Jbene M

20 mai 2018

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

par Leonid G

26 mars 2018

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

par Ramil G

25 mars 2019

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

par Andrés V

19 avr. 2021

Intense, detailed approach to sophisticated techniques. Recommended.

par Reto G

7 juil. 2021

E​xcellent course, advanced level, packed with valuable information

par CARLOS A R R

22 nov. 2020

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

par Thamalu P

31 août 2020

A very good course focusing practical stuff on model enhancement.

par Resve S

27 juil. 2018

Highly recommended for those wanting to be an advanced Kaggler!

par Angel D

30 sept. 2019

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

par Aldo D

6 avr. 2020

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

par Adithya N

18 nov. 2019

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

par Lionel C

18 févr. 2018

Awesome, Excellent.

It gives many tricks for a data scientist.

par Aymen B S

19 mai 2019

very good courses makes me learn a lot practical examples