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How to Win a Data Science Competition: Learn from Top Kagglers(으)로 돌아가기

HSE 대학의 How to Win a Data Science Competition: Learn from Top Kagglers 학습자 리뷰 및 피드백

1,113개의 평가
274개의 리뷰

강좌 소개

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:

최상위 리뷰

2018년 3월 28일

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!

2019년 2월 18일

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.

필터링 기준:

How to Win a Data Science Competition: Learn from Top Kagglers의 273개 리뷰 중 201~225

교육 기관: Masamune I

2021년 12월 20일

Wonderful course!

교육 기관: Evgeny V

2021년 3월 13일

It was quite hard

교육 기관: Mauricio A

2017년 11월 19일

Very nice tricks!

교육 기관: Alexis S

2019년 2월 4일

Very good course

교육 기관: himanshu t

2018년 1월 23일

really great..!!


2018년 7월 21일

awesome course

교육 기관: Aditya S

2018년 5월 1일

Amazing Course

교육 기관: Anti L

2021년 8월 22일

Great course!

교육 기관: MD A R A

2020년 8월 26일

Excellent !!!

교육 기관: Mike K

2019년 1월 17일

Отличный курс

교육 기관: Ivan S

2019년 1월 12일

Great course!

교육 기관: carlos a g b

2020년 4월 12일

good content

교육 기관: Amandeep S

2019년 1월 13일

Great Course

교육 기관: PC P K

2018년 5월 17일

great course

교육 기관: Jorge F R

2020년 10월 19일


교육 기관: harsh n

2018년 1월 21일

Hammer lol

교육 기관: Sourav S

2020년 8월 28일

Thank You

교육 기관: Ricardo M B

2020년 6월 28일


교육 기관: Марчевский В Д

2018년 9월 12일

Good one!

교육 기관: Alexey B

2018년 3월 19일

Good job!

교육 기관: Kirill K

2021년 2월 4일








교육 기관: Krishna H

2020년 8월 7일


교육 기관: Cindy N P P

2020년 7월 19일


교육 기관: Nicolas M

2020년 3월 20일