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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!

2017년 11월 9일

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.

필터링 기준:

How to Win a Data Science Competition: Learn from Top Kagglers의 273개 리뷰 중 126~150

교육 기관: superfantastic

2018년 11월 6일

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

교육 기관: Willian W

2018년 5월 20일

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

교육 기관: John F P

2020년 11월 22일

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

교육 기관: Atul S

2020년 5월 11일

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

교육 기관: mar m

2019년 8월 19일

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

교육 기관: Nguyen V L

2020년 5월 7일

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

교육 기관: Denis R

2020년 5월 5일

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

교육 기관: James T

2018년 5월 7일

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

교육 기관: CINTHYA G C G

2020년 7월 23일

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

교육 기관: Mostafa M M

2019년 1월 7일

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

교육 기관: Eric S

2020년 10월 15일

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

교육 기관: Wesley A B J

2019년 3월 16일

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

교육 기관: Jbene M

2018년 5월 20일

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

교육 기관: Leonid G

2018년 3월 26일

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

교육 기관: Ramil G

2019년 3월 25일

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

교육 기관: Andrés V

2021년 4월 19일

Intense, detailed approach to sophisticated techniques. Recommended.

교육 기관: Reto G

2021년 7월 7일

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

교육 기관: CARLOS A R R

2020년 11월 22일

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

교육 기관: Thamalu P

2020년 8월 31일

A very good course focusing practical stuff on model enhancement.

교육 기관: Resve S

2018년 7월 27일

Highly recommended for those wanting to be an advanced Kaggler!

교육 기관: Angel D

2019년 9월 30일

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

교육 기관: Aldo D

2020년 4월 6일

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

교육 기관: Adithya N

2019년 11월 18일

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

교육 기관: Lionel C

2018년 2월 18일

Awesome, Excellent.

It gives many tricks for a data scientist.

교육 기관: Aymen B S

2019년 5월 19일

very good courses makes me learn a lot practical examples