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[CourseClub.NET] Coursera - How to Win a Data Science Competition Learn from Top Kagglers
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文档列表
001.Welcome to How to win a data science competition/001. Introduction.mp4
10.2 MB
001.Welcome to How to win a data science competition/001. Introduction.srt
2.8 kB
001.Welcome to How to win a data science competition/002. Meet your lecturers.mp4
14.5 MB
001.Welcome to How to win a data science competition/002. Meet your lecturers.srt
3.6 kB
001.Welcome to How to win a data science competition/003. Course overview.mp4
36.3 MB
001.Welcome to How to win a data science competition/003. Course overview.srt
10.4 kB
002.Competition mechanics/004. Competition Mechanics.mp4
26.1 MB
002.Competition mechanics/004. Competition Mechanics.srt
11.2 kB
002.Competition mechanics/005. Kaggle Overview [screencast].mp4
33.9 MB
002.Competition mechanics/005. Kaggle Overview [screencast].srt
9.4 kB
002.Competition mechanics/006. Real World Application vs Competitions.mp4
21.0 MB
002.Competition mechanics/006. Real World Application vs Competitions.srt
8.9 kB
003.Recap of main ML algorithms/007. Recap of main ML algorithms.mp4
35.1 MB
003.Recap of main ML algorithms/007. Recap of main ML algorithms.srt
13.9 kB
004.Software Hardware requirements/008. Software Hardware Requirements.mp4
22.6 MB
004.Software Hardware requirements/008. Software Hardware Requirements.srt
8.1 kB
005.Feature preprocessing and generation with respect to models/009. Overview.mp4
26.9 MB
005.Feature preprocessing and generation with respect to models/009. Overview.srt
9.2 kB
005.Feature preprocessing and generation with respect to models/010. Numeric features.mp4
50.7 MB
005.Feature preprocessing and generation with respect to models/010. Numeric features.srt
19.0 kB
005.Feature preprocessing and generation with respect to models/011. Categorical and ordinal features.mp4
42.5 MB
005.Feature preprocessing and generation with respect to models/011. Categorical and ordinal features.srt
13.5 kB
005.Feature preprocessing and generation with respect to models/012. Datetime and coordinates.mp4
34.0 MB
005.Feature preprocessing and generation with respect to models/012. Datetime and coordinates.srt
10.5 kB
005.Feature preprocessing and generation with respect to models/013. Handling missing values.mp4
39.7 MB
005.Feature preprocessing and generation with respect to models/013. Handling missing values.srt
13.1 kB
006.Feature extraction from text and images/014. Bag of words.mp4
39.9 MB
006.Feature extraction from text and images/014. Bag of words.srt
14.0 kB
006.Feature extraction from text and images/015. Word2vec, CNN.mp4
48.2 MB
006.Feature extraction from text and images/015. Word2vec, CNN.srt
17.2 kB
007.Final project/016. Final project overview.mp4
18.7 MB
007.Final project/016. Final project overview.srt
5.6 kB
008.Exploratory data analysis/017. Exploratory data analysis.mp4
25.1 MB
008.Exploratory data analysis/017. Exploratory data analysis.srt
9.9 kB
008.Exploratory data analysis/018. Building intuition about the data.mp4
23.4 MB
008.Exploratory data analysis/018. Building intuition about the data.srt
9.7 kB
008.Exploratory data analysis/019. Exploring anonymized data.mp4
45.1 MB
008.Exploratory data analysis/019. Exploring anonymized data.srt
18.6 kB
008.Exploratory data analysis/020. Visualizations.mp4
44.7 MB
008.Exploratory data analysis/020. Visualizations.srt
16.5 kB
008.Exploratory data analysis/021. Dataset cleaning and other things to check.mp4
27.1 MB
008.Exploratory data analysis/021. Dataset cleaning and other things to check.srt
9.8 kB
009.EDA examples/022. Springleaf competition EDA I.mp4
21.1 MB
009.EDA examples/022. Springleaf competition EDA I.srt
9.2 kB
009.EDA examples/023. Springleaf competition EDA II.mp4
46.5 MB
009.EDA examples/023. Springleaf competition EDA II.srt
20.3 kB
009.EDA examples/024. Numerai competition EDA.mp4
23.0 MB
009.EDA examples/024. Numerai competition EDA.srt
7.9 kB
010.Validation/025. Validation and overfitting.mp4
35.7 MB
010.Validation/025. Validation and overfitting.srt
13.6 kB
010.Validation/026. Validation strategies.mp4
27.4 MB
010.Validation/026. Validation strategies.srt
9.3 kB
010.Validation/027. Data splitting strategies.mp4
58.9 MB
010.Validation/027. Data splitting strategies.srt
19.1 kB
010.Validation/028. Problems occurring during validation.mp4
74.5 MB
010.Validation/028. Problems occurring during validation.srt
26.0 kB
011.Data leakages/029. Basic data leaks.mp4
23.2 MB
011.Data leakages/029. Basic data leaks.srt
8.3 kB
011.Data leakages/030. Leaderboard probing and examples of rare data leaks.mp4
35.7 MB
011.Data leakages/030. Leaderboard probing and examples of rare data leaks.srt
12.5 kB
011.Data leakages/031. Expedia challenge.mp4
37.4 MB
011.Data leakages/031. Expedia challenge.srt
11.7 kB
012.Metrics optimization/032. Motivation.mp4
28.8 MB
012.Metrics optimization/032. Motivation.srt
10.8 kB
012.Metrics optimization/033. Regression metrics review I.mp4
48.6 MB
012.Metrics optimization/033. Regression metrics review I.srt
17.9 kB
012.Metrics optimization/034. Regression metrics review II.mp4
30.6 MB
012.Metrics optimization/034. Regression metrics review II.srt
9.8 kB
012.Metrics optimization/035. Classification metrics review.mp4
73.7 MB
012.Metrics optimization/035. Classification metrics review.srt
24.8 kB
012.Metrics optimization/036. General approaches for metrics optimization.mp4
24.9 MB
012.Metrics optimization/036. General approaches for metrics optimization.srt
8.2 kB
012.Metrics optimization/037. Regression metrics optimization.mp4
37.6 MB
012.Metrics optimization/037. Regression metrics optimization.srt
12.4 kB
012.Metrics optimization/038. Classification metrics optimization I.mp4
27.5 MB
012.Metrics optimization/038. Classification metrics optimization I.srt
9.2 kB
012.Metrics optimization/039. Classification metrics optimization II.mp4
26.5 MB
012.Metrics optimization/039. Classification metrics optimization II.srt
8.9 kB
013.Mean encodings/040. Concept of mean encoding.mp4
32.0 MB
013.Mean encodings/040. Concept of mean encoding.srt
10.1 kB
013.Mean encodings/041. Regularization.mp4
29.7 MB
013.Mean encodings/041. Regularization.srt
9.4 kB
013.Mean encodings/042. Extensions and generalizations.mp4
41.1 MB
013.Mean encodings/042. Extensions and generalizations.srt
12.5 kB
014.Hyperparameter tuning/043. Hyperparameter tuning I.mp4
26.2 MB
014.Hyperparameter tuning/043. Hyperparameter tuning I.srt
9.1 kB
014.Hyperparameter tuning/044. Hyperparameter tuning II.mp4
45.4 MB
014.Hyperparameter tuning/044. Hyperparameter tuning II.srt
15.5 kB
014.Hyperparameter tuning/045. Hyperparameter tuning III.mp4
49.5 MB
014.Hyperparameter tuning/045. Hyperparameter tuning III.srt
15.5 kB
015.Tips and tricks/046. Practical guide.mp4
62.0 MB
015.Tips and tricks/046. Practical guide.srt
22.7 kB
015.Tips and tricks/047. KazAnova's competition pipeline, part 1.mp4
35.5 MB
015.Tips and tricks/047. KazAnova's competition pipeline, part 1.srt
24.0 kB
015.Tips and tricks/048. KazAnova's competition pipeline, part 2.mp4
33.6 MB
015.Tips and tricks/048. KazAnova's competition pipeline, part 2.srt
22.1 kB
016.Advanced features II/049. Statistics and distance based features.mp4
22.0 MB
016.Advanced features II/049. Statistics and distance based features.srt
7.0 kB
016.Advanced features II/050. Matrix factorizations.mp4
25.3 MB
016.Advanced features II/050. Matrix factorizations.srt
9.2 kB
016.Advanced features II/051. Feature Interactions.mp4
21.4 MB
016.Advanced features II/051. Feature Interactions.srt
8.0 kB
016.Advanced features II/052. t-SNE.mp4
22.6 MB
016.Advanced features II/052. t-SNE.srt
7.7 kB
017.Ensembling/053. Introduction into ensemble methods.mp4
11.2 MB
017.Ensembling/053. Introduction into ensemble methods.srt
7.2 kB
017.Ensembling/054. Bagging.mp4
16.7 MB
017.Ensembling/054. Bagging.srt
11.3 kB
017.Ensembling/055. Boosting.mp4
29.3 MB
017.Ensembling/055. Boosting.srt
19.6 kB
017.Ensembling/056. Stacking.mp4
32.3 MB
017.Ensembling/056. Stacking.srt
19.4 kB
017.Ensembling/057. StackNet.mp4
30.7 MB
017.Ensembling/057. StackNet.srt
18.5 kB
017.Ensembling/058. Ensembling Tips and Tricks.mp4
26.8 MB
017.Ensembling/058. Ensembling Tips and Tricks.srt
18.4 kB
018.Competitions go through/059. Crowdflower Competition.mp4
37.9 MB
018.Competitions go through/059. Crowdflower Competition.srt
15.8 kB
018.Competitions go through/060. Springleaf Marketing Response.mp4
25.4 MB
018.Competitions go through/060. Springleaf Marketing Response.srt
8.1 kB
018.Competitions go through/061. Microsoft Malware Classification Challenge.mp4
71.7 MB
018.Competitions go through/061. Microsoft Malware Classification Challenge.srt
23.5 kB
018.Competitions go through/062. Walmart Trip Type Classification.mp4
31.0 MB
018.Competitions go through/062. Walmart Trip Type Classification.srt
10.2 kB
018.Competitions go through/063. Acquire Valued Shoppers Challenge, part 1.mp4
36.5 MB
018.Competitions go through/063. Acquire Valued Shoppers Challenge, part 1.srt
25.7 kB
018.Competitions go through/064. Acquire Valued Shoppers Challenge, part 2.mp4
32.4 MB
018.Competitions go through/064. Acquire Valued Shoppers Challenge, part 2.srt
22.4 kB
[CourseClub.NET].url
123 Bytes
[FCS Forum].url
133 Bytes
[FreeCourseSite.com].url
127 Bytes
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