种子简介

种子名称： [FreeCourseSite.com] Udemy - Machine Learning Practical 6 Real-World Applications
文件类型： 视频
文件数目： 78个文件
文件大小： 4.05 GB
收录时间： 2021-11-14 06:33
已经下载： 3次
资源热度： 128
最近下载： 2024-5-6 00:31

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:5e5e1b7b8c9b0c778014c5937ea0b8880c933899&dn=[FreeCourseSite.com] Udemy - Machine Learning Practical 6 Real-World Applications 复制链接到迅雷、QQ旋风进行下载，或者使用百度云离线下载。

喜欢这个种子的人也喜欢

种子包含的文件

[FreeCourseSite.com] Udemy - Machine Learning Practical 6 Real-World Applications.torrent

1. Introduction/1. Welcome to the course!.mp436.75MB

2. Breast Cancer Classification/1. Introduction.mp414.97MB

2. Breast Cancer Classification/2. Business Challenge.mp460.98MB

2. Breast Cancer Classification/3. Updates on Udemy Reviews.mp456.12MB

2. Breast Cancer Classification/4. Challenge in Machine Learning Vocabulary.mp479.06MB

2. Breast Cancer Classification/5. Data Visualisation.mp4140.5MB

2. Breast Cancer Classification/6. Model Training.mp470.94MB

2. Breast Cancer Classification/7. Model Evaluation.mp491.38MB

2. Breast Cancer Classification/8. Improving the Model.mp4189.77MB

2. Breast Cancer Classification/9. Conclusion.mp424.04MB

3. Fashion Class Classification/1. Business Challenge.mp492.22MB

3. Fashion Class Classification/10. Conclusion.mp455.27MB

3. Fashion Class Classification/2. Challenge in Machine Learning Vocabulary.mp469.24MB

3. Fashion Class Classification/3. Data Visualisation.mp4130.14MB

3. Fashion Class Classification/4. Model Training Part I.mp4103.76MB

3. Fashion Class Classification/5. Model Training Part II.mp478.3MB

3. Fashion Class Classification/6. Model Training Part III.mp4125.99MB

3. Fashion Class Classification/7. Model Training Part IV.mp4128.19MB

3. Fashion Class Classification/8. Model Evaluation.mp473.61MB

3. Fashion Class Classification/9. Improving the Model.mp431.62MB

4. Directing Customers to Subscription Through App Behavior Analysis/1. Fintech Case Studies Introduction.mp414.63MB

4. Directing Customers to Subscription Through App Behavior Analysis/10. Model Building.mp472.33MB

4. Directing Customers to Subscription Through App Behavior Analysis/11. Model Conclusion.mp429.99MB

4. Directing Customers to Subscription Through App Behavior Analysis/12. Final Remarks.mp419.05MB

4. Directing Customers to Subscription Through App Behavior Analysis/2. Introduction.mp418.28MB

4. Directing Customers to Subscription Through App Behavior Analysis/3. Data.mp453.63MB

4. Directing Customers to Subscription Through App Behavior Analysis/4. Features Histograms.mp460.84MB

4. Directing Customers to Subscription Through App Behavior Analysis/5. Correlation Plot.mp422.04MB

4. Directing Customers to Subscription Through App Behavior Analysis/6. Correlation Matrix.mp432.28MB

4. Directing Customers to Subscription Through App Behavior Analysis/7. Feature Engineering - Response.mp454.89MB

4. Directing Customers to Subscription Through App Behavior Analysis/8. Feature Engineering - Screens.mp471.04MB

4. Directing Customers to Subscription Through App Behavior Analysis/9. Data Pre-Processing.mp460.65MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/1. Introduction.mp419.6MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/10. Model Building.mp451.26MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/11. K-Fold Cross Validation.mp431.69MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/12. Feature Selection.mp464.3MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/13. Model Conclusion.mp438.42MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/14. Final Remarks.mp424.29MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/2. Data.mp477.48MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/3. Data Cleaning.mp432.56MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/4. Features Histograms.mp450.24MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/5. Pie Chart Distributions.mp470.58MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/6. Correlation Plot.mp448.74MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/7. Correlation Matrix.mp456.1MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/8. One-Hot Encoding.mp442.89MB

5. Minimizing Churn Rate Through Analysis of Financial Habits/9. Feature Scaling & Balancing.mp479.72MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/1. Introduction.mp475.13MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/10. Model Building Part 2.mp493.45MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/11. Grid Search Part 1.mp474.43MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/12. Grid Search Part 2.mp498.07MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/13. Model Conclusion.mp418.31MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/14. Final Remarks.mp430.57MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/2. Data.mp4101.91MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/3. Data Housekeeping.mp444.08MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/4. Histograms.mp450.81MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/5. Correlation Plot.mp424.28MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/6. Correlation Matrix.mp433.41MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/7. Feature Engineering.mp423.47MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/8. Data Preprocessing.mp460.17MB

6. Predicting the Likelihood of E-Signing a Loan Based on Financial History/9. Model Building Part 1.mp458.77MB

7. Credit Card Fraud Detection/1. Case Study.mp430.08MB

7. Credit Card Fraud Detection/10. Metrics.mp415.11MB

7. Credit Card Fraud Detection/11. Confusion Matrix.mp440.06MB

7. Credit Card Fraud Detection/12. Machine Learning Classifiers.mp434.17MB

7. Credit Card Fraud Detection/13. Random Forest.mp431.02MB

7. Credit Card Fraud Detection/14. Decision Trees.mp418.77MB

7. Credit Card Fraud Detection/15. Sampling.mp47.74MB

7. Credit Card Fraud Detection/16. Undersampling.mp436.92MB

7. Credit Card Fraud Detection/17. Smote.mp435.71MB

7. Credit Card Fraud Detection/18. Final remarks.mp419.06MB

7. Credit Card Fraud Detection/2. Machine Learning Vocabulary.mp422.95MB

7. Credit Card Fraud Detection/3. Set Up.mp423.92MB

7. Credit Card Fraud Detection/4. Data Visualization.mp420.4MB

7. Credit Card Fraud Detection/5. Data Preprocessing.mp439.03MB

7. Credit Card Fraud Detection/6. Deep Learning Part 1.mp423.22MB

7. Credit Card Fraud Detection/7. Deep Learning Part 2.mp448.19MB

7. Credit Card Fraud Detection/8. Splitting the Data.mp438.21MB

7. Credit Card Fraud Detection/9. Training.mp421.19MB