搜索
[GigaCourse.Com] Udemy - Business Data Analytics & Intelligence with Python 2023
磁力链接/BT种子名称
[GigaCourse.Com] Udemy - Business Data Analytics & Intelligence with Python 2023
磁力链接/BT种子简介
种子哈希:
b2ddb6c6b78581345be1b6d7e3bdaed969d29bed
文件大小:
6.18G
已经下载:
688
次
下载速度:
极快
收录时间:
2023-12-28
最近下载:
2024-11-07
移花宫入口
移花宫.com
邀月.com
怜星.com
花无缺.com
yhgbt.icu
yhgbt.top
磁力链接下载
magnet:?xt=urn:btih:B2DDB6C6B78581345BE1B6D7E3BDAED969D29BED
推荐使用
PIKPAK网盘
下载资源,10TB超大空间,不限制资源,无限次数离线下载,视频在线观看
下载BT种子文件
磁力链接
迅雷下载
PIKPAK在线播放
91视频
含羞草
欲漫涩
逼哩逼哩
成人快手
51品茶
抖阴破解版
暗网禁地
91短视频
TikTok成人版
PornHub
草榴社区
乱伦社区
最近搜索
old man multi
2384199
人瘦奶大
juvr-134
メスダチ the animation 千紗編
本郷爱
naked 2018
black angel
ryua-shuji
tppn-099
best child
艳母孟若羽
老婆
4558460
rdt-234
jordanlake
sweet dreams footjob
fc2-ppv-4538719
[ladyboygold] panya
jade+amor
jul-909
cawd-648
bewitched
naked 2018 satya dusaugey
sisloves me
09.10
081409_590
纸箱厂厕拍
猎冰第十集
ne zha 2019
文件列表
9. Google Causal Impact (Econometrics and Causal Inference)/22. CHALLENGE Solutions.mp4
172.4 MB
13. Gaussian Mixture/14. CHALLENGE Solutions.mp4
168.4 MB
16. Facebook Prophet/33. CHALLENGE Solutions (Part 3).mp4
134.0 MB
16. Facebook Prophet/32. CHALLENGE Solutions (Part 2).mp4
117.0 MB
6. Multilinear Regression/22. CHALLENGE Solutions.mp4
116.0 MB
10. Matching/24. CHALLENGE Solutions.mp4
112.7 MB
7. Logistic Regression/20. CHALLENGE Solutions.mp4
95.0 MB
13. Gaussian Mixture/12. Python - Interpretation.mp4
82.5 MB
1. Introduction/3. Join Our Online Classroom!.mp4
79.0 MB
9. Google Causal Impact (Econometrics and Causal Inference)/16. Python - Correlation Matrix and Heatmap.mp4
77.9 MB
12. RFM (Recency, Frequency, Monetary) Analysis/18. CHALLENGE Solutions.mp4
76.2 MB
16. Facebook Prophet/31. CHALLENGE Solutions (Part 1).mp4
72.6 MB
10. Matching/13. Python - Transforming Race Variable.mp4
69.4 MB
4. Intermediary Statistics/20. Python - T-test.mp4
68.7 MB
16. Facebook Prophet/17. Python - Facebook Prophet.mp4
63.9 MB
16. Facebook Prophet/28. Python - Parameter Tuning.mp4
63.8 MB
16. Facebook Prophet/20. Python - Event Assessment.mp4
63.2 MB
3. Basic Statistics/5. Python - Mean.mp4
62.6 MB
15. Random Forest/21. CHALLENGE Solutions (Part 2).mp4
62.0 MB
1. Introduction/5. Setting up the Course Material.mp4
60.8 MB
9. Google Causal Impact (Econometrics and Causal Inference)/15. Python - Stationarity.mp4
60.7 MB
16. Facebook Prophet/19. Python - Forecasting.mp4
60.5 MB
7. Logistic Regression/13. Python - Function to Read Coefficients.mp4
59.4 MB
10. Matching/21. Python - Matching Robustness Repeated Samples.mp4
58.9 MB
16. Facebook Prophet/24. Python - Cross-Validation.mp4
58.7 MB
15. Random Forest/20. CHALLENGE Solutions (Part 1).mp4
58.6 MB
3. Basic Statistics/13. Python - Correlation.mp4
56.7 MB
1. Introduction/1. Python for Business Analytics & Intelligence.mp4
56.2 MB
3. Basic Statistics/4. Python - Directory, Libraries and Data.mp4
53.8 MB
4. Intermediary Statistics/9. Python - Shapiro-Wilks Test.mp4
53.6 MB
4. Intermediary Statistics/23. Python - Chi-square test.mp4
52.9 MB
10. Matching/19. Python - Matching Model.mp4
52.7 MB
7. Logistic Regression/6. Python - Histogram and Outlier Removal.mp4
50.6 MB
15. Random Forest/18. Python - Parameter Tuning.mp4
50.5 MB
16. Facebook Prophet/22. Python - Visualization.mp4
50.2 MB
10. Matching/9. Python - T-Test Loop.mp4
49.6 MB
16. Facebook Prophet/25. Python - Cross-Validation Results and Visualization.mp4
48.5 MB
4. Intermediary Statistics/16. Python - Confidence Interval.mp4
48.0 MB
1. Introduction/7. ZTM Resources.mp4
46.7 MB
4. Intermediary Statistics/15. Confidence interval.mp4
45.0 MB
6. Multilinear Regression/17. Python - Multilinear Regression.mp4
44.8 MB
9. Google Causal Impact (Econometrics and Causal Inference)/20. Python - Causal Impact Results.mp4
43.9 MB
12. RFM (Recency, Frequency, Monetary) Analysis/12. Python - Quartiles.mp4
43.9 MB
9. Google Causal Impact (Econometrics and Causal Inference)/9. Python - Load Bitcoin Price Data.mp4
43.1 MB
4. Intermediary Statistics/5. Python - Normal Distribution Visualization.mp4
42.9 MB
9. Google Causal Impact (Econometrics and Causal Inference)/21. CHALLENGE Introduction.mp4
42.5 MB
6. Multilinear Regression/7. Python - Plotting Continuous Variables.mp4
41.3 MB
9. Google Causal Impact (Econometrics and Causal Inference)/23. EXERCISE Imposter Syndrome.mp4
41.1 MB
13. Gaussian Mixture/9. Python - Optimal Number of Clusters.mp4
40.6 MB
7. Logistic Regression/17. Python - Manual Accuracy Assessment.mp4
40.3 MB
9. Google Causal Impact (Econometrics and Causal Inference)/12. Python - Data Preparation.mp4
40.2 MB
10. Matching/14. Python - Transforming Education Variable.mp4
40.0 MB
6. Multilinear Regression/20. Python - Accuracy Assessment.mp4
39.4 MB
16. Facebook Prophet/11. Python - Black Friday Holiday.mp4
39.3 MB
16. Facebook Prophet/29. Python - Parameter Tuning Results.mp4
38.6 MB
5. Linear Regression/12. EXERCISE Python - Linear Regression.mp4
37.8 MB
10. Matching/8. Python - T-Test.mp4
37.1 MB
10. Matching/23. CHALLENGE Introduction.mp4
36.0 MB
16. Facebook Prophet/27. Python - Parameter Grid.mp4
35.8 MB
5. Linear Regression/7. Linear Regression Output.mp4
35.1 MB
10. Matching/18. Python - Plotting Common Support Region.mp4
34.7 MB
13. Gaussian Mixture/13. CHALLENGE Introduction.mp4
34.5 MB
6. Multilinear Regression/4. Python - Preparing Script and Loading Data.mp4
34.4 MB
16. Facebook Prophet/6. Python - Loading and Inspecting the Data.mp4
34.2 MB
4. Intermediary Statistics/21. EXERCISE Python - T-test.mp4
33.5 MB
15. Random Forest/11. Python - Training and Test Set.mp4
33.2 MB
9. Google Causal Impact (Econometrics and Causal Inference)/18. Python - Google Causal Impact.mp4
32.6 MB
12. RFM (Recency, Frequency, Monetary) Analysis/9. Python - Customer Level Aggregation.mp4
31.9 MB
7. Logistic Regression/16. Python - Confusion Matrix.mp4
31.1 MB
10. Matching/16. Common Support Region.mp4
30.9 MB
3. Basic Statistics/12. Correlation.mp4
30.8 MB
16. Facebook Prophet/18. Python - Regressor Coefficients.mp4
30.7 MB
16. Facebook Prophet/21. Python - Accuracy Assessment.mp4
30.7 MB
7. Logistic Regression/19. CHALLENGE Introduction.mp4
30.7 MB
15. Random Forest/19. CHALLENGE Introduction.mp4
30.6 MB
10. Matching/11. Python - Chi-square Loop.mp4
30.4 MB
4. Intermediary Statistics/12. Python - Standard Error.mp4
30.2 MB
4. Intermediary Statistics/4. Python - Preparing Script and Loading Data.mp4
30.0 MB
9. Google Causal Impact (Econometrics and Causal Inference)/8. Python - Dates.mp4
29.8 MB
4. Intermediary Statistics/6. EXERCISE Python - Normal Distribution.mp4
29.7 MB
6. Multilinear Regression/10. Python - For Loop.mp4
29.6 MB
7. Logistic Regression/5. Python - Summary Statistics.mp4
29.3 MB
7. Logistic Regression/4. Python - Preparing Script and Loading Data.mp4
29.2 MB
6. Multilinear Regression/21. CHALLENGE Introduction.mp4
29.0 MB
5. Linear Regression/4. Python - Preparing Script and Loading Data.mp4
28.8 MB
12. RFM (Recency, Frequency, Monetary) Analysis/16. Python - Results Summary.mp4
28.6 MB
4. Intermediary Statistics/7. P-value.mp4
28.6 MB
10. Matching/5. Python - Loading Data.mp4
28.6 MB
6. Multilinear Regression/9. Python - Categorical Variables.mp4
27.8 MB
10. Matching/17. Python - Logistic Regression for Common Support Region.mp4
27.6 MB
5. Linear Regression/9. Python - Plotting Regression.mp4
27.4 MB
15. Random Forest/15. Python - Feature Importance.mp4
27.3 MB
9. Google Causal Impact (Econometrics and Causal Inference)/19. Interpreting the Causal Impact Plots.mp4
26.8 MB
3. Basic Statistics/8. Python - Median.mp4
26.6 MB
15. Random Forest/14. Python - Classification Report and F1 score.mp4
25.9 MB
7. Logistic Regression/15. Confusion Matrix.mp4
25.7 MB
3. Basic Statistics/14. EXERCISE Python - Correlation.mp4
25.3 MB
15. Random Forest/8. Python - Summary Statistics.mp4
24.7 MB
12. RFM (Recency, Frequency, Monetary) Analysis/6. Python - Loading Data.mp4
24.6 MB
9. Google Causal Impact (Econometrics and Causal Inference)/11. Python - Loading More Stock Data.mp4
24.4 MB
10. Matching/10. Python - Chi-square Test.mp4
24.3 MB
10. Matching/4. Python - Libraries and Directory.mp4
23.9 MB
4. Intermediary Statistics/24. EXERCISE Python - Chi-square.mp4
23.8 MB
16. Facebook Prophet/10. Python - Easter Holiday.mp4
23.5 MB
12. RFM (Recency, Frequency, Monetary) Analysis/14. Python - RFM Function.mp4
23.5 MB
5. Linear Regression/8. Python - Linear Regression model and summary.mp4
23.0 MB
12. RFM (Recency, Frequency, Monetary) Analysis/8. Python - Date Variable.mp4
22.9 MB
7. Logistic Regression/10. Python - Training and Test Set.mp4
22.7 MB
7. Logistic Regression/14. Python - Predictions.mp4
22.3 MB
6. Multilinear Regression/8. Python - Correlation Matrix.mp4
22.1 MB
6. Multilinear Regression/12. Python - Isolate X and Y.mp4
21.7 MB
3. Basic Statistics/9. EXERCISE Python - Median.mp4
21.3 MB
9. Google Causal Impact (Econometrics and Causal Inference)/7. Python - Libraries and Dates.mp4
21.1 MB
15. Random Forest/6. Python - Loading Data.mp4
20.7 MB
10. Matching/22. Python - Removing 1 Confounder.mp4
20.6 MB
7. Logistic Regression/18. Python - Classification Report.mp4
20.5 MB
1. Introduction/6. The Modern Day Business Analyst.mp4
20.5 MB
3. Basic Statistics/10. Python - Mode.mp4
19.7 MB
6. Multilinear Regression/5. Python - Summary Statistics.mp4
19.7 MB
12. RFM (Recency, Frequency, Monetary) Analysis/11. Python - Tidying up Dataframe.mp4
19.6 MB
7. Logistic Regression/12. Python - Logistic Regression.mp4
19.5 MB
10. Matching/2. Matching.mp4
19.5 MB
9. Google Causal Impact (Econometrics and Causal Inference)/1. Why Econometrics and Causal Inference.mp4
19.2 MB
16. Facebook Prophet/7. Python - Transforming Date Variable.mp4
18.9 MB
12. RFM (Recency, Frequency, Monetary) Analysis/17. CHALLENGE Introduction.mp4
18.8 MB
5. Linear Regression/11. Python - Dummy Variable.mp4
18.7 MB
15. Random Forest/12. Python - Random Forest Model.mp4
18.7 MB
15. Random Forest/17. Python - Parameter Grid.mp4
18.6 MB
3. Basic Statistics/16. Python - Standard Deviation.mp4
18.5 MB
6. Multilinear Regression/11. Python - Creating Dummy Variables.mp4
18.4 MB
9. Google Causal Impact (Econometrics and Causal Inference)/14. Correlation Recap and Stationarity.mp4
18.2 MB
7. Logistic Regression/8. Python - Transforming Dependent Variable.mp4
18.2 MB
15. Random Forest/3. How Decision Trees Work.mp4
18.1 MB
10. Matching/15. Python - Cleaning and Preparing Dataframe.mp4
18.0 MB
17. Where To Go From Here/1. Thank You!.mp4
17.7 MB
10. Matching/7. Python - Comparing Means per Group.mp4
17.5 MB
9. Google Causal Impact (Econometrics and Causal Inference)/10. Assumptions.mp4
17.5 MB
13. Gaussian Mixture/6. Python - Load Data.mp4
17.4 MB
16. Facebook Prophet/30. CHALLENGE Introduction - Demand in NYC.mp4
17.4 MB
3. Basic Statistics/6. EXERCISE Python - Mean.mp4
17.3 MB
5. Linear Regression/3. Linear Regression.mp4
17.0 MB
4. Intermediary Statistics/17. EXERCISE Python - Confidence Interval.mp4
16.9 MB
12. RFM (Recency, Frequency, Monetary) Analysis/7. Python - Creating Sales Variable.mp4
16.8 MB
4. Intermediary Statistics/25. Powerposing and p-hacking.mp4
16.5 MB
12. RFM (Recency, Frequency, Monetary) Analysis/15. Python - Applying RFM Function.mp4
16.5 MB
16. Facebook Prophet/34. Forecasting at Uber.mp4
16.4 MB
9. Google Causal Impact (Econometrics and Causal Inference)/13. Python - Training Dataframe.mp4
16.3 MB
9. Google Causal Impact (Econometrics and Causal Inference)/17. Python - Google Causal Impact Setup.mp4
15.9 MB
16. Facebook Prophet/5. Python - Directory and Libraries.mp4
15.8 MB
7. Logistic Regression/7. Python - Correlation Matrix.mp4
15.8 MB
4. Intermediary Statistics/10. EXERCISE Python - Shapiro-Wilks.mp4
15.8 MB
13. Gaussian Mixture/5. Python - Directory and Data.mp4
15.4 MB
6. Multilinear Regression/18. Accuracy KPIs (Key Performance Indicators).mp4
15.3 MB
12. RFM (Recency, Frequency, Monetary) Analysis/3. RFM Model.mp4
15.1 MB
13. Gaussian Mixture/11. Python - Cluster Prediction and Assignment.mp4
15.0 MB
9. Google Causal Impact (Econometrics and Causal Inference)/4. CASE STUDY Bitcoin and PayPal (Briefing).mp4
15.0 MB
12. RFM (Recency, Frequency, Monetary) Analysis/5. Python - Directory and Libraries.mp4
14.9 MB
15. Random Forest/5. Python - Directory and Libraries.mp4
14.6 MB
6. Multilinear Regression/16. Python - Train and Test Split.mp4
14.6 MB
13. Gaussian Mixture/3. Gaussian Mixture Model.mp4
14.5 MB
15. Random Forest/7. Python - Transform Object into Numerical Variables.mp4
14.2 MB
15. Random Forest/10. Python - Isolate X and Y.mp4
13.7 MB
13. Gaussian Mixture/15. My Experience with Segmentation.mp4
13.6 MB
4. Intermediary Statistics/2. Normal Distribution.mp4
13.4 MB
3. Basic Statistics/11. EXERCISE Python - Mode.mp4
13.2 MB
4. Intermediary Statistics/13. EXERCISE Python - Standard Error.mp4
13.2 MB
3. Basic Statistics/18. CASE STUDY Moneyball.mp4
13.1 MB
10. Matching/6. Unconfoundedness.mp4
12.8 MB
5. Linear Regression/10. Dummy Variable Trap.mp4
12.7 MB
16. Facebook Prophet/3. Facebook Prophet.mp4
12.7 MB
12. RFM (Recency, Frequency, Monetary) Analysis/13. Python - RFM Score.mp4
12.6 MB
13. Gaussian Mixture/7. Python - Transform Character variables.mp4
12.6 MB
9. Google Causal Impact (Econometrics and Causal Inference)/5. Difference-in-Differences Framework.mp4
12.2 MB
7. Logistic Regression/9. Python - Prepare X and Y.mp4
12.1 MB
5. Linear Regression/6. Python - Adding Constant.mp4
12.0 MB
5. Linear Regression/5. Python - Isolate X and Y.mp4
11.6 MB
7. Logistic Regression/11. How to Read Logistic Regression Coefficients.mp4
11.4 MB
16. Facebook Prophet/15. Facebook Prophet Model.mp4
11.4 MB
16. Facebook Prophet/14. Python - Training and Test Set.mp4
11.2 MB
13. Gaussian Mixture/8. AIC and BIC.mp4
10.6 MB
16. Facebook Prophet/16. Additive vs. Multiplicative Seasonality.mp4
10.6 MB
7. Logistic Regression/3. Logistic Regression.mp4
10.6 MB
4. Intermediary Statistics/3. CASE STUDY Wine Quality (Briefing).mp4
10.3 MB
6. Multilinear Regression/19. Python - Model Predictions.mp4
10.2 MB
10. Matching/12. The Curse of Dimensionality.mp4
9.8 MB
3. Basic Statistics/2. Arithmetic Mean.mp4
9.5 MB
15. Random Forest/2. Ensemble Learning and Random Forest.mp4
9.5 MB
12. RFM (Recency, Frequency, Monetary) Analysis/2. Value Based Segmentation.mp4
9.4 MB
16. Facebook Prophet/8. Python - Renaming Variables.mp4
9.4 MB
10. Matching/1. Matching - Game Plan.mp4
9.3 MB
6. Multilinear Regression/6. Outliers.mp4
9.2 MB
4. Intermediary Statistics/22. Chi-square test.mp4
9.2 MB
13. Gaussian Mixture/10. Python - Gaussian Mixture Model.mp4
9.0 MB
16. Facebook Prophet/9. Dynamic Holidays.mp4
8.9 MB
4. Intermediary Statistics/14. Z-Score.mp4
8.9 MB
10. Matching/3. CASE STUDY Catholic Schools & Standardized Tests (Briefing).mp4
8.9 MB
3. Basic Statistics/7. Median and Mode.mp4
8.8 MB
12. RFM (Recency, Frequency, Monetary) Analysis/10. Python - Monetary Variable.mp4
8.7 MB
16. Facebook Prophet/12. Python - Finishing Holiday Preparation.mp4
8.7 MB
16. Facebook Prophet/26. Parameters to Tune.mp4
8.7 MB
16. Facebook Prophet/2. Structural Time Series.mp4
8.6 MB
4. Intermediary Statistics/11. Standard Error of the Mean.mp4
8.5 MB
15. Random Forest/13. Python - Predictions.mp4
8.2 MB
10. Matching/25. My Experience with Matching.mp4
8.1 MB
15. Random Forest/16. Parameter Tuning.mp4
8.0 MB
1. Introduction/2. Introduction.mp4
7.6 MB
3. Basic Statistics/15. Standard Deviation.mp4
7.6 MB
6. Multilinear Regression/13. Python - Adding Constant.mp4
7.4 MB
15. Random Forest/9. Random Forest Quirks.mp4
7.0 MB
10. Matching/20. Matching Robustness Check.mp4
7.0 MB
4. Intermediary Statistics/18. T-test.mp4
6.9 MB
3. Basic Statistics/17. EXERCISE Python - Standard Deviation.mp4
6.8 MB
9. Google Causal Impact (Econometrics and Causal Inference)/3. Time Series Data.mp4
6.7 MB
13. Gaussian Mixture/2. Clustering.mp4
6.5 MB
4. Intermediary Statistics/8. Shapiro-Wilks Test.mp4
6.4 MB
9. Google Causal Impact (Econometrics and Causal Inference)/6. Causal Impact Step-by-Step Guide.mp4
6.2 MB
16. Facebook Prophet/13. Training and Test Set in Time Series.mp4
6.1 MB
6. Multilinear Regression/2. The Concept of Multilinear Regression.mp4
5.6 MB
6. Multilinear Regression/14. Under and Over Fitting.mp4
5.3 MB
16. Facebook Prophet/1. Facebook Prophet - Game Plan.mp4
5.3 MB
6. Multilinear Regression/1. Multilinear Regression - Game Plan.mp4
4.4 MB
9. Google Causal Impact (Econometrics and Causal Inference)/2. Google Causal Impact - Game Plan.mp4
4.2 MB
16. Facebook Prophet/23. Cross-Validation.mp4
3.8 MB
5. Linear Regression/1. Linear Regression - Game Plan.mp4
3.8 MB
16. Facebook Prophet/4. CASE STUDY Wikipedia (Briefing).mp4
3.7 MB
5. Linear Regression/2. CASE STUDY Diamonds (Briefing).mp4
3.5 MB
15. Random Forest/1. Random Forest - Game Plan.mp4
3.5 MB
7. Logistic Regression/1. Logistic Regression - Game Plan.mp4
3.3 MB
6. Multilinear Regression/3. CASE STUDY Professors' Salary (Briefing).mp4
3.2 MB
13. Gaussian Mixture/4. CASE STUDY Credit Cards #1 (Briefing).mp4
3.1 MB
7. Logistic Regression/2. CASE STUDY Spam Emails (Briefing).mp4
3.1 MB
12. RFM (Recency, Frequency, Monetary) Analysis/4. CASE STUDY Online Shopping (Briefing).mp4
3.1 MB
3. Basic Statistics/1. Basic Statistics - Game Plan.mp4
3.1 MB
6. Multilinear Regression/15. Training and Test Set.mp4
2.9 MB
13. Gaussian Mixture/1. Gaussian Mixture - Game Plan.mp4
2.8 MB
4. Intermediary Statistics/19. CASE STUDY Remote Work Predictions (Briefing).mp4
2.6 MB
12. RFM (Recency, Frequency, Monetary) Analysis/1. RFM - Game Plan.mp4
2.4 MB
15. Random Forest/4. CASE STUDY Credit Cards #2 (Briefing).mp4
2.3 MB
3. Basic Statistics/3. CASE STUDY Moneyball (Briefing).mp4
2.3 MB
4. Intermediary Statistics/1. Intermediary Statistics - Game Plan.mp4
1.9 MB
9. Google Causal Impact (Econometrics and Causal Inference)/22. CHALLENGE Solutions.srt
22.2 kB
13. Gaussian Mixture/14. CHALLENGE Solutions.srt
20.2 kB
6. Multilinear Regression/22. CHALLENGE Solutions.srt
20.0 kB
16. Facebook Prophet/33. CHALLENGE Solutions (Part 3).srt
17.3 kB
16. Facebook Prophet/32. CHALLENGE Solutions (Part 2).srt
16.7 kB
10. Matching/24. CHALLENGE Solutions.srt
16.4 kB
7. Logistic Regression/20. CHALLENGE Solutions.srt
15.6 kB
12. RFM (Recency, Frequency, Monetary) Analysis/18. CHALLENGE Solutions.srt
13.1 kB
4. Intermediary Statistics/20. Python - T-test.srt
12.4 kB
16. Facebook Prophet/31. CHALLENGE Solutions (Part 1).srt
12.1 kB
3. Basic Statistics/13. Python - Correlation.srt
10.6 kB
3. Basic Statistics/5. Python - Mean.srt
10.6 kB
15. Random Forest/21. CHALLENGE Solutions (Part 2).srt
10.5 kB
9. Google Causal Impact (Econometrics and Causal Inference)/16. Python - Correlation Matrix and Heatmap.srt
10.5 kB
7. Logistic Regression/13. Python - Function to Read Coefficients.srt
10.3 kB
1. Introduction/5. Setting up the Course Material.srt
10.0 kB
10. Matching/13. Python - Transforming Race Variable.srt
9.8 kB
3. Basic Statistics/4. Python - Directory, Libraries and Data.srt
9.7 kB
15. Random Forest/20. CHALLENGE Solutions (Part 1).srt
9.5 kB
10. Matching/21. Python - Matching Robustness Repeated Samples.srt
9.4 kB
4. Intermediary Statistics/5. Python - Normal Distribution Visualization.srt
9.3 kB
13. Gaussian Mixture/12. Python - Interpretation.srt
9.2 kB
4. Intermediary Statistics/9. Python - Shapiro-Wilks Test.srt
9.1 kB
4. Intermediary Statistics/23. Python - Chi-square test.srt
8.9 kB
9. Google Causal Impact (Econometrics and Causal Inference)/15. Python - Stationarity.srt
8.9 kB
16. Facebook Prophet/20. Python - Event Assessment.srt
8.4 kB
16. Facebook Prophet/28. Python - Parameter Tuning.srt
8.4 kB
16. Facebook Prophet/19. Python - Forecasting.srt
8.1 kB
16. Facebook Prophet/22. Python - Visualization.srt
8.1 kB
7. Logistic Regression/6. Python - Histogram and Outlier Removal.srt
8.1 kB
10. Matching/19. Python - Matching Model.srt
7.9 kB
4. Intermediary Statistics/16. Python - Confidence Interval.srt
7.9 kB
15. Random Forest/18. Python - Parameter Tuning.srt
7.8 kB
7. Logistic Regression/17. Python - Manual Accuracy Assessment.srt
7.6 kB
7. Logistic Regression/15. Confusion Matrix.srt
7.5 kB
16. Facebook Prophet/25. Python - Cross-Validation Results and Visualization.srt
7.4 kB
16. Facebook Prophet/24. Python - Cross-Validation.srt
7.4 kB
12. RFM (Recency, Frequency, Monetary) Analysis/12. Python - Quartiles.srt
7.3 kB
16. Facebook Prophet/17. Python - Facebook Prophet.srt
7.2 kB
4. Intermediary Statistics/6. EXERCISE Python - Normal Distribution.srt
7.0 kB
4. Intermediary Statistics/7. P-value.srt
6.8 kB
13. Gaussian Mixture/9. Python - Optimal Number of Clusters.srt
6.7 kB
6. Multilinear Regression/20. Python - Accuracy Assessment.srt
6.7 kB
5. Linear Regression/12. EXERCISE Python - Linear Regression.srt
6.5 kB
1. Introduction/7. ZTM Resources.srt
6.5 kB
10. Matching/23. CHALLENGE Introduction.srt
6.5 kB
9. Google Causal Impact (Econometrics and Causal Inference)/21. CHALLENGE Introduction.srt
6.4 kB
4. Intermediary Statistics/15. Confidence interval.srt
6.4 kB
16. Facebook Prophet/11. Python - Black Friday Holiday.srt
6.4 kB
9. Google Causal Impact (Econometrics and Causal Inference)/20. Python - Causal Impact Results.srt
6.3 kB
12. RFM (Recency, Frequency, Monetary) Analysis/3. RFM Model.srt
6.2 kB
16. Facebook Prophet/6. Python - Loading and Inspecting the Data.srt
6.2 kB
16. Facebook Prophet/10. Python - Easter Holiday.srt
6.2 kB
4. Intermediary Statistics/21. EXERCISE Python - T-test.srt
6.1 kB
1. Introduction/3. Join Our Online Classroom!.srt
6.1 kB
10. Matching/9. Python - T-Test Loop.srt
6.0 kB
6. Multilinear Regression/4. Python - Preparing Script and Loading Data.srt
6.0 kB
4. Intermediary Statistics/4. Python - Preparing Script and Loading Data.srt
6.0 kB
5. Linear Regression/4. Python - Preparing Script and Loading Data.srt
5.7 kB
16. Facebook Prophet/27. Python - Parameter Grid.srt
5.7 kB
5. Linear Regression/3. Linear Regression.srt
5.7 kB
1. Introduction/6. The Modern Day Business Analyst.srt
5.6 kB
9. Google Causal Impact (Econometrics and Causal Inference)/12. Python - Data Preparation.srt
5.6 kB
10. Matching/18. Python - Plotting Common Support Region.srt
5.6 kB
7. Logistic Regression/16. Python - Confusion Matrix.srt
5.6 kB
10. Matching/14. Python - Transforming Education Variable.srt
5.6 kB
6. Multilinear Regression/7. Python - Plotting Continuous Variables.srt
5.6 kB
3. Basic Statistics/12. Correlation.srt
5.5 kB
16. Facebook Prophet/21. Python - Accuracy Assessment.srt
5.5 kB
16. Facebook Prophet/34. Forecasting at Uber.srt
5.5 kB
6. Multilinear Regression/21. CHALLENGE Introduction.srt
5.5 kB
6. Multilinear Regression/17. Python - Multilinear Regression.srt
5.4 kB
3. Basic Statistics/8. Python - Median.srt
5.2 kB
13. Gaussian Mixture/13. CHALLENGE Introduction.srt
5.2 kB
12. RFM (Recency, Frequency, Monetary) Analysis/16. Python - Results Summary.srt
5.1 kB
9. Google Causal Impact (Econometrics and Causal Inference)/9. Python - Load Bitcoin Price Data.srt
5.1 kB
10. Matching/17. Python - Logistic Regression for Common Support Region.srt
5.1 kB
6. Multilinear Regression/10. Python - For Loop.srt
5.0 kB
15. Random Forest/15. Python - Feature Importance.srt
5.0 kB
6. Multilinear Regression/9. Python - Categorical Variables.srt
5.0 kB
7. Logistic Regression/19. CHALLENGE Introduction.srt
5.0 kB
10. Matching/8. Python - T-Test.srt
5.0 kB
9. Google Causal Impact (Econometrics and Causal Inference)/8. Python - Dates.srt
4.9 kB
10. Matching/16. Common Support Region.srt
4.9 kB
7. Logistic Regression/4. Python - Preparing Script and Loading Data.srt
4.8 kB
12. RFM (Recency, Frequency, Monetary) Analysis/14. Python - RFM Function.srt
4.8 kB
15. Random Forest/19. CHALLENGE Introduction.srt
4.8 kB
9. Google Causal Impact (Econometrics and Causal Inference)/14. Correlation Recap and Stationarity.srt
4.7 kB
4. Intermediary Statistics/12. Python - Standard Error.srt
4.7 kB
15. Random Forest/3. How Decision Trees Work.srt
4.6 kB
5. Linear Regression/9. Python - Plotting Regression.srt
4.6 kB
9. Google Causal Impact (Econometrics and Causal Inference)/23. EXERCISE Imposter Syndrome.srt
4.6 kB
9. Google Causal Impact (Econometrics and Causal Inference)/1. Why Econometrics and Causal Inference.srt
4.6 kB
9. Google Causal Impact (Econometrics and Causal Inference)/19. Interpreting the Causal Impact Plots.srt
4.6 kB
9. Google Causal Impact (Econometrics and Causal Inference)/11. Python - Loading More Stock Data.srt
4.5 kB
13. Gaussian Mixture/3. Gaussian Mixture Model.srt
4.4 kB
16. Facebook Prophet/3. Facebook Prophet.srt
4.3 kB
6. Multilinear Regression/12. Python - Isolate X and Y.srt
4.3 kB
3. Basic Statistics/18. CASE STUDY Moneyball.srt
4.3 kB
3. Basic Statistics/14. EXERCISE Python - Correlation.srt
4.3 kB
16. Facebook Prophet/29. Python - Parameter Tuning Results.srt
4.2 kB
5. Linear Regression/11. Python - Dummy Variable.srt
4.1 kB
10. Matching/11. Python - Chi-square Loop.srt
4.1 kB
12. RFM (Recency, Frequency, Monetary) Analysis/9. Python - Customer Level Aggregation.srt
4.1 kB
16. Facebook Prophet/7. Python - Transforming Date Variable.srt
4.1 kB
4. Intermediary Statistics/25. Powerposing and p-hacking.srt
4.0 kB
12. RFM (Recency, Frequency, Monetary) Analysis/17. CHALLENGE Introduction.srt
4.0 kB
9. Google Causal Impact (Econometrics and Causal Inference)/10. Assumptions.srt
4.0 kB
10. Matching/2. Matching.srt
4.0 kB
12. RFM (Recency, Frequency, Monetary) Analysis/8. Python - Date Variable.srt
3.9 kB
5. Linear Regression/10. Dummy Variable Trap.srt
3.9 kB
13. Gaussian Mixture/15. My Experience with Segmentation.srt
3.9 kB
5. Linear Regression/7. Linear Regression Output.srt
3.9 kB
10. Matching/10. Python - Chi-square Test.srt
3.8 kB
1. Introduction/4. Exercise Meet Your Classmates + Instructor.html
3.8 kB
3. Basic Statistics/9. EXERCISE Python - Median.srt
3.8 kB
15. Random Forest/14. Python - Classification Report and F1 score.srt
3.8 kB
4. Intermediary Statistics/24. EXERCISE Python - Chi-square.srt
3.8 kB
9. Google Causal Impact (Econometrics and Causal Inference)/7. Python - Libraries and Dates.srt
3.8 kB
5. Linear Regression/8. Python - Linear Regression model and summary.srt
3.7 kB
16. Facebook Prophet/18. Python - Regressor Coefficients.srt
3.6 kB
7. Logistic Regression/14. Python - Predictions.srt
3.6 kB
15. Random Forest/17. Python - Parameter Grid.srt
3.6 kB
6. Multilinear Regression/11. Python - Creating Dummy Variables.srt
3.6 kB
9. Google Causal Impact (Econometrics and Causal Inference)/5. Difference-in-Differences Framework.srt
3.6 kB
1. Introduction/1. Python for Business Analytics & Intelligence.srt
3.5 kB
6. Multilinear Regression/18. Accuracy KPIs (Key Performance Indicators).srt
3.5 kB
4. Intermediary Statistics/2. Normal Distribution.srt
3.5 kB
15. Random Forest/11. Python - Training and Test Set.srt
3.5 kB
6. Multilinear Regression/5. Python - Summary Statistics.srt
3.4 kB
10. Matching/15. Python - Cleaning and Preparing Dataframe.srt
3.4 kB
3. Basic Statistics/10. Python - Mode.srt
3.4 kB
12. RFM (Recency, Frequency, Monetary) Analysis/2. Value Based Segmentation.srt
3.4 kB
6. Multilinear Regression/8. Python - Correlation Matrix.srt
3.4 kB
9. Google Causal Impact (Econometrics and Causal Inference)/18. Python - Google Causal Impact.srt
3.4 kB
7. Logistic Regression/5. Python - Summary Statistics.srt
3.4 kB
10. Matching/4. Python - Libraries and Directory.srt
3.4 kB
6. Multilinear Regression/6. Outliers.srt
3.4 kB
3. Basic Statistics/7. Median and Mode.srt
3.4 kB
5. Linear Regression/6. Python - Adding Constant.srt
3.4 kB
4. Intermediary Statistics/10. EXERCISE Python - Shapiro-Wilks.srt
3.3 kB
15. Random Forest/12. Python - Random Forest Model.srt
3.3 kB
10. Matching/25. My Experience with Matching.srt
3.2 kB
4. Intermediary Statistics/11. Standard Error of the Mean.srt
3.2 kB
4. Intermediary Statistics/3. CASE STUDY Wine Quality (Briefing).srt
3.2 kB
13. Gaussian Mixture/11. Python - Cluster Prediction and Assignment.srt
3.1 kB
10. Matching/1. Matching - Game Plan.srt
3.1 kB
4. Intermediary Statistics/13. EXERCISE Python - Standard Error.srt
3.1 kB
10. Matching/22. Python - Removing 1 Confounder.srt
3.1 kB
12. RFM (Recency, Frequency, Monetary) Analysis/6. Python - Loading Data.srt
3.0 kB
15. Random Forest/16. Parameter Tuning.srt
3.0 kB
4. Intermediary Statistics/14. Z-Score.srt
3.0 kB
12. RFM (Recency, Frequency, Monetary) Analysis/11. Python - Tidying up Dataframe.srt
3.0 kB
7. Logistic Regression/8. Python - Transforming Dependent Variable.srt
3.0 kB
10. Matching/7. Python - Comparing Means per Group.srt
3.0 kB
16. Facebook Prophet/5. Python - Directory and Libraries.srt
3.0 kB
7. Logistic Regression/10. Python - Training and Test Set.srt
3.0 kB
16. Facebook Prophet/15. Facebook Prophet Model.srt
2.9 kB
10. Matching/6. Unconfoundedness.srt
2.9 kB
4. Intermediary Statistics/22. Chi-square test.srt
2.9 kB
7. Logistic Regression/18. Python - Classification Report.srt
2.9 kB
7. Logistic Regression/11. How to Read Logistic Regression Coefficients.srt
2.9 kB
16. Facebook Prophet/2. Structural Time Series.srt
2.8 kB
15. Random Forest/9. Random Forest Quirks.srt
2.8 kB
16. Facebook Prophet/9. Dynamic Holidays.srt
2.8 kB
16. Facebook Prophet/16. Additive vs. Multiplicative Seasonality.srt
2.8 kB
10. Matching/5. Python - Loading Data.srt
2.8 kB
9. Google Causal Impact (Econometrics and Causal Inference)/4. CASE STUDY Bitcoin and PayPal (Briefing).srt
2.7 kB
3. Basic Statistics/15. Standard Deviation.srt
2.7 kB
12. RFM (Recency, Frequency, Monetary) Analysis/15. Python - Applying RFM Function.srt
2.7 kB
3. Basic Statistics/16. Python - Standard Deviation.srt
2.7 kB
4. Intermediary Statistics/17. EXERCISE Python - Confidence Interval.srt
2.7 kB
3. Basic Statistics/2. Arithmetic Mean.srt
2.7 kB
6. Multilinear Regression/16. Python - Train and Test Split.srt
2.7 kB
7. Logistic Regression/12. Python - Logistic Regression.srt
2.6 kB
7. Logistic Regression/7. Python - Correlation Matrix.srt
2.6 kB
4. Intermediary Statistics/18. T-test.srt
2.6 kB
15. Random Forest/8. Python - Summary Statistics.srt
2.6 kB
7. Logistic Regression/9. Python - Prepare X and Y.srt
2.6 kB
15. Random Forest/2. Ensemble Learning and Random Forest.srt
2.6 kB
9. Google Causal Impact (Econometrics and Causal Inference)/17. Python - Google Causal Impact Setup.srt
2.5 kB
13. Gaussian Mixture/2. Clustering.srt
2.5 kB
15. Random Forest/5. Python - Directory and Libraries.srt
2.5 kB
16. Facebook Prophet/30. CHALLENGE Introduction - Demand in NYC.srt
2.5 kB
3. Basic Statistics/6. EXERCISE Python - Mean.srt
2.5 kB
9. Google Causal Impact (Econometrics and Causal Inference)/6. Causal Impact Step-by-Step Guide.srt
2.5 kB
13. Gaussian Mixture/8. AIC and BIC.srt
2.5 kB
16. Facebook Prophet/26. Parameters to Tune.srt
2.5 kB
1. Introduction/2. Introduction.srt
2.4 kB
12. RFM (Recency, Frequency, Monetary) Analysis/5. Python - Directory and Libraries.srt
2.4 kB
10. Matching/20. Matching Robustness Check.srt
2.3 kB
16. Facebook Prophet/13. Training and Test Set in Time Series.srt
2.3 kB
16. Facebook Prophet/14. Python - Training and Test Set.srt
2.3 kB
6. Multilinear Regression/2. The Concept of Multilinear Regression.srt
2.2 kB
7. Logistic Regression/3. Logistic Regression.srt
2.2 kB
13. Gaussian Mixture/5. Python - Directory and Data.srt
2.2 kB
9. Google Causal Impact (Econometrics and Causal Inference)/13. Python - Training Dataframe.srt
2.2 kB
4. Intermediary Statistics/8. Shapiro-Wilks Test.srt
2.1 kB
10. Matching/12. The Curse of Dimensionality.srt
2.1 kB
13. Gaussian Mixture/6. Python - Load Data.srt
2.1 kB
15. Random Forest/6. Python - Loading Data.srt
2.1 kB
11. PART C SEGMENTATION/1. What is Segmentation and why is it important.html
2.1 kB
16. Facebook Prophet/1. Facebook Prophet - Game Plan.srt
2.0 kB
5. Linear Regression/5. Python - Isolate X and Y.srt
2.0 kB
15. Random Forest/7. Python - Transform Object into Numerical Variables.srt
2.0 kB
12. RFM (Recency, Frequency, Monetary) Analysis/13. Python - RFM Score.srt
2.0 kB
12. RFM (Recency, Frequency, Monetary) Analysis/7. Python - Creating Sales Variable.srt
2.0 kB
3. Basic Statistics/11. EXERCISE Python - Mode.srt
2.0 kB
16. Facebook Prophet/8. Python - Renaming Variables.srt
1.9 kB
17. Where To Go From Here/1. Thank You!.srt
1.9 kB
10. Matching/3. CASE STUDY Catholic Schools & Standardized Tests (Briefing).srt
1.9 kB
6. Multilinear Regression/1. Multilinear Regression - Game Plan.srt
1.8 kB
15. Random Forest/10. Python - Isolate X and Y.srt
1.8 kB
8. PART B ECONOMETRICS & CAUSAL INFERENCE/1. What are Econometrics & Causal Inference, and why are they important.html
1.8 kB
6. Multilinear Regression/19. Python - Model Predictions.srt
1.8 kB
5. Linear Regression/1. Linear Regression - Game Plan.srt
1.7 kB
9. Google Causal Impact (Econometrics and Causal Inference)/2. Google Causal Impact - Game Plan.srt
1.7 kB
6. Multilinear Regression/14. Under and Over Fitting.srt
1.7 kB
14. PART D PREDICTIVE ANALYTICS/1. What are Predictive Analytics and why are they important.html
1.7 kB
6. Multilinear Regression/13. Python - Adding Constant.srt
1.7 kB
9. Google Causal Impact (Econometrics and Causal Inference)/3. Time Series Data.srt
1.7 kB
1. Introduction/8. Monthly Coding Challenges, Free Resources and Guides.html
1.6 kB
2. PART A STATISTICS/1. What are Statistics and why are they important.html
1.6 kB
15. Random Forest/13. Python - Predictions.srt
1.5 kB
16. Facebook Prophet/12. Python - Finishing Holiday Preparation.srt
1.5 kB
13. Gaussian Mixture/1. Gaussian Mixture - Game Plan.srt
1.4 kB
7. Logistic Regression/1. Logistic Regression - Game Plan.srt
1.4 kB
17. Where To Go From Here/3. Endorsements On LinkedIn.html
1.4 kB
13. Gaussian Mixture/10. Python - Gaussian Mixture Model.srt
1.4 kB
12. RFM (Recency, Frequency, Monetary) Analysis/10. Python - Monetary Variable.srt
1.4 kB
13. Gaussian Mixture/7. Python - Transform Character variables.srt
1.4 kB
3. Basic Statistics/17. EXERCISE Python - Standard Deviation.srt
1.3 kB
3. Basic Statistics/1. Basic Statistics - Game Plan.srt
1.3 kB
3. Basic Statistics/3. CASE STUDY Moneyball (Briefing).srt
1.3 kB
16. Facebook Prophet/23. Cross-Validation.srt
1.3 kB
18. BONUS Section/1. Special Bonus Lecture.html
1.3 kB
15. Random Forest/1. Random Forest - Game Plan.srt
1.2 kB
6. Multilinear Regression/15. Training and Test Set.srt
1.2 kB
16. Facebook Prophet/4. CASE STUDY Wikipedia (Briefing).srt
1.1 kB
5. Linear Regression/2. CASE STUDY Diamonds (Briefing).srt
1.1 kB
7. Logistic Regression/2. CASE STUDY Spam Emails (Briefing).srt
1.1 kB
12. RFM (Recency, Frequency, Monetary) Analysis/4. CASE STUDY Online Shopping (Briefing).srt
1.1 kB
13. Gaussian Mixture/4. CASE STUDY Credit Cards #1 (Briefing).srt
1.1 kB
6. Multilinear Regression/3. CASE STUDY Professors' Salary (Briefing).srt
1.0 kB
4. Intermediary Statistics/1. Intermediary Statistics - Game Plan.srt
971 Bytes
17. Where To Go From Here/2. Become An Alumni.html
921 Bytes
4. Intermediary Statistics/19. CASE STUDY Remote Work Predictions (Briefing).srt
875 Bytes
15. Random Forest/4. CASE STUDY Credit Cards #2 (Briefing).srt
860 Bytes
17. Where To Go From Here/5. Coding Challenges.html
860 Bytes
12. RFM (Recency, Frequency, Monetary) Analysis/1. RFM - Game Plan.srt
849 Bytes
17. Where To Go From Here/4. Learning Guideline.html
353 Bytes
0. Websites you may like/[CourseClub.Me].url
122 Bytes
1. Introduction/[CourseClub.Me].url
122 Bytes
14. PART D PREDICTIVE ANALYTICS/[CourseClub.Me].url
122 Bytes
7. Logistic Regression/[CourseClub.Me].url
122 Bytes
[CourseClub.Me].url
122 Bytes
1. Introduction/7.1 LinkedIn Group.html
102 Bytes
1. Introduction/5.1 Course Materials.html
99 Bytes
1. Introduction/7.3 ZTM Youtube.html
99 Bytes
1. Introduction/7.2 zerotomastery.io.html
86 Bytes
1. Introduction/5.2 Sign up for your free Google Drive account here..html
85 Bytes
0. Websites you may like/[GigaCourse.Com].url
49 Bytes
1. Introduction/[GigaCourse.Com].url
49 Bytes
14. PART D PREDICTIVE ANALYTICS/[GigaCourse.Com].url
49 Bytes
7. Logistic Regression/[GigaCourse.Com].url
49 Bytes
[GigaCourse.Com].url
49 Bytes
随机展示
相关说明
本站不存储任何资源内容,只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符),并提供查询服务,是一个完全合法的搜索引擎系统。 网站不提供种子下载服务,用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责,请用户注意甄别!
>