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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

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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: coursera@hse.ru...

Principales revisiones

MS

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!

MM

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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151 - 175 de 224 revisiones para How to Win a Data Science Competition: Learn from Top Kagglers

por Yury A

Oct 09, 2019

thanks for this course, well done!

por Sergiy M

Apr 23, 2020

Hands-on, very practical course.

por Nakamura T

Jul 10, 2020

programming assignment is good.

por Raheel H

Aug 06, 2020

A great learning experience.

por JOHN F V O

Sep 12, 2020

Good and demanding curse

por Akshit J

Jul 28, 2020

Really insightful course.

por Yingxin W

Apr 18, 2020

A lot of good materials

por Maniar T G

Sep 26, 2019

Amazing Course. Thanks!

por Boris G A

Jun 23, 2020

Hiper super course :D

por sagar s

Sep 29, 2018

Awesome. Worth it!.

por Ujjwal U

Jan 27, 2018

Exceptional course!

por Moti T

Jan 04, 2018

Interesting and fun

por Chiang y

Jul 26, 2018

Excellent class!!!

por GUO S

Jul 23, 2018

Like it very much!

por Mauricio D A

Nov 19, 2017

Very nice tricks!

por Diego G

Feb 04, 2019

Very good course

por himanshu t

Jan 23, 2018

really great..!!

por PRASHANT K R

Jul 21, 2018

awesome course

por Aditya S

May 01, 2018

Amazing Course

por MD A R A

Aug 26, 2020

Excellent !!!

por Mike K

Jan 17, 2019

Отличный курс

por Ivan S

Jan 12, 2019

Great course!

por carlos a g b

Apr 12, 2020

good content

por Amandeep S

Jan 14, 2019

Great Course

por PC P K

May 17, 2018

great course