Download [Coursera] How to Win a Data Science Competition: Learn from Top Kagglers torrent

[Coursera] How to Win a Data Science Competition: Learn from Top Kagglers

Torrent:	[Coursera] How to Win a Data Science Competition: Learn from Top Kagglers
Description:	[Coursera] How to Win a Data Science Competition: Learn from Top Kagglers If you want to break into competitive data science, then this course is for you! For More Courses: https://courseclub.net
Downloads:	96
Category:	Other /Tutorials
Size:	2 GB
Show Files »	[CourseClub.NET] Coursera - How to Win a Data Science Competition Learn from Top Kagglers 001.Welcome to How to win a data science competition 001. Introduction.mp4 (9.7 MB) 001. Introduction.srt (2.7 KB) 002. Meet your lecturers.mp4 (13.8 MB) 002. Meet your lecturers.srt (3.6 KB) 003. Course overview.mp4 (34.6 MB) 003. Course overview.srt (10.2 KB) 002.Competition mechanics 004. Competition Mechanics.mp4 (24.9 MB) 004. Competition Mechanics.srt (10.9 KB) 005. Kaggle Overview [screencast].mp4 (32.4 MB) 005. Kaggle Overview [screencast].srt (9.2 KB) 006. Real World Application vs Competitions.mp4 (20.0 MB) 006. Real World Application vs Competitions.srt (8.7 KB) 003.Recap of main ML algorithms 007. Recap of main ML algorithms.mp4 (33.4 MB) 007. Recap of main ML algorithms.srt (13.6 KB) 004.Software Hardware requirements 008. Software Hardware Requirements.mp4 (21.5 MB) 008. Software Hardware Requirements.srt (7.9 KB) 005.Feature preprocessing and generation with respect to models 009. Overview.mp4 (25.7 MB) 009. Overview.srt (9.0 KB) 010. Numeric features.mp4 (48.3 MB) 010. Numeric features.srt (18.6 KB) 011. Categorical and ordinal features.mp4 (40.5 MB) 011. Categorical and ordinal features.srt (13.2 KB) 012. Datetime and coordinates.mp4 (32.4 MB) 012. Datetime and coordinates.srt (10.2 KB) 013. Handling missing values.mp4 (37.9 MB) 013. Handling missing values.srt (12.8 KB) 006.Feature extraction from text and images 014. Bag of words.mp4 (38.0 MB) 014. Bag of words.srt (13.7 KB) 015. Word2vec, CNN.mp4 (46.0 MB) 015. Word2vec, CNN.srt (16.8 KB) 007.Final project 016. Final project overview.mp4 (17.8 MB) 016. Final project overview.srt (5.4 KB) 008.Exploratory data analysis 017. Exploratory data analysis.mp4 (24.0 MB) 017. Exploratory data analysis.srt (9.7 KB) 018. Building intuition about the data.mp4 (22.3 MB) 018. Building intuition about the data.srt (9.4 KB) 019. Exploring anonymized data.mp4 (43.0 MB) 019. Exploring anonymized data.srt (18.2 KB) 020. Visualizations.mp4 (42.6 MB) 020. Visualizations.srt (16.1 KB) 021. Dataset cleaning and other things to check.mp4 (25.8 MB) 021. Dataset cleaning and other things to check.srt (9.6 KB) 009.EDA examples 022. Springleaf competition EDA I.mp4 (20.1 MB) 022. Springleaf competition EDA I.srt (9.0 KB) 023. Springleaf competition EDA II.mp4 (44.4 MB) 023. Springleaf competition EDA II.srt (19.9 KB) 024. Numerai competition EDA.mp4 (22.0 MB) 024. Numerai competition EDA.srt (7.7 KB) 010.Validation 025. Validation and overfitting.mp4 (34.1 MB) 025. Validation and overfitting.srt (13.3 KB) 026. Validation strategies.mp4 (26.1 MB) 026. Validation strategies.srt (9.1 KB) 027. Data splitting strategies.mp4 (56.2 MB) 027. Data splitting strategies.srt (18.7 KB) 028. Problems occurring during validation.mp4 (71.0 MB) 028. Problems occurring during validation.srt (25.4 KB) 011.Data leakages 029. Basic data leaks.mp4 (22.1 MB) 029. Basic data leaks.srt (8.1 KB) 030. Leaderboard probing and examples of rare data leaks.mp4 (34.1 MB) 030. Leaderboard probing and examples of rare data leaks.srt (12.2 KB) 031. Expedia challenge.mp4 (35.7 MB) 031. Expedia challenge.srt (11.4 KB) 012.Metrics optimization 032. Motivation.mp4 (27.5 MB) 032. Motivation.srt (10.6 KB) 033. Regression metrics review I.mp4 (46.4 MB) 033. Regression metrics review I.srt (17.5 KB) 034. Regression metrics review II.mp4 (29.2 MB) 034. Regression metrics review II.srt (9.5 KB) 035. Classification metrics review.mp4 (70.3 MB) 035. Classification metrics review.srt (24.3 KB) 036. General approaches for metrics optimization.mp4 (23.7 MB) 036. General approaches for metrics optimization.srt (8.0 KB) 037. Regression metrics optimization.mp4 (35.8 MB) 037. Regression metrics optimization.srt (12.1 KB) 038. Classification metrics optimization I.mp4 (26.3 MB) 038. Classification metrics optimization I.srt (8.9 KB) 039. Classification metrics optimization II.mp4 (25.2 MB) 039. Classification metrics optimization II.srt (8.7 KB) 013.Mean encodings 040. Concept of mean encoding.mp4 (30.5 MB) 040. Concept of mean encoding.srt (9.9 KB) 041. Regularization.mp4 (28.4 MB) 041. Regularization.srt (9.2 KB) 042. Extensions and generalizations.mp4 (39.2 MB) 042. Extensions and generalizations.srt (12.2 KB) 014.Hyperparameter tuning 043. Hyperparameter tuning I.mp4 (25.0 MB) 043. Hyperparameter tuning I.srt (8.8 KB) 044. Hyperparameter tuning II.mp4 (43.3 MB) 044. Hyperparameter tuning II.srt (15.1 KB) 045. Hyperparameter tuning III.mp4 (47.2 MB) 045. Hyperparameter tuning III.srt (15.2 KB) 015.Tips and tricks 046. Practical guide.mp4 (59.1 MB) 046. Practical guide.srt (22.2 KB) 047. KazAnova's competition pipeline, part 1.mp4 (33.8 MB) 047. KazAnova's competition pipeline, part 1.srt (23.4 KB) 048. KazAnova's competition pipeline, part 2.mp4 (32.0 MB) 048. KazAnova's competition pipeline, part 2.srt (21.6 KB) 016.Advanced features II files
Added:	2018-10-08 02:05:07
Language:	English
Peers:	Seeders : 19 , Leechers : 17
Tags:	Coursera How to Win a Data Science Competition Learn from Top Kagglers
Release name:	[Coursera] How to Win a Data Science Competition: Learn from Top Kagglers
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