Torrent details for "Logistic Regression in Python" Log in to bookmark
Controls:
×
Report Torrent
Please select a reason for reporting this torrent:
Your report will be reviewed by our moderation team.
×
Report Information
Loading report information...
This torrent has been reported 0 times.
Report Summary:
| User | Reason | Date |
|---|
Failed to load report information.
×
Success
Your report has been submitted successfully.
Checked by:
Category:
Language:
English
Total Size:
102 bytes
Info Hash:
B78B34440BBB1EB48BAB857AD689B8AF827C606C
Added By:
Added:
July 23, 2026, 3:06 a.m.
Stats:
|
(Last updated: July 23, 2026, 3:06 a.m.)
| File | Size |
|---|---|
| Bonus Resources.txt | 102 bytes |
| Get Bonus Downloads Here.url | 204 bytes |
| 1 - 00-Introduction-01-py.pdf | 472.2 KB |
| 1 - Welcome To The Course.mp4 | 25.3 MB |
| 2 - Course Resources.html | 102 bytes |
| Customer.csv | 64.0 KB |
| House-Price.csv | 50.6 KB |
| Classification.ipynb | 171.7 KB |
| 02_whynot_linear.pdf | 155.3 KB |
| 03_logistic.pdf | 352.7 KB |
| 04_.pdf | 165.3 KB |
| 04_P_value.pdf | 228.0 KB |
| 05_Multiple_predictors.pdf | 151.3 KB |
| 06_Confusion matrix.pdf | 222.3 KB |
| 07_LDA.pdf | 183.1 KB |
| 08_ROC.pdf | 306.9 KB |
| 09_KNN.pdf | 236.7 KB |
| 76 - The Problem Statement.mp4 | 14.2 MB |
| 77 - Basic Equations And Ordinary Least Squares Ols Method.mp4 | 65.1 MB |
| 78 - Assessing Accuracy Of Predicted Coefficients.mp4 | 139.8 MB |
| 79 - Assessing Model Accuracy Rse And R Squared.mp4 | 66.6 MB |
| 80 - Simple Linear Regression In Python.mp4 | 89.7 MB |
| 81 - Multiple Linear Regression.mp4 | 52.4 MB |
| 82 - The F Statistic.mp4 | 86.7 MB |
| 83 - Interpreting Results Of Categorical Variables.mp4 | 33.6 MB |
| 84 - Multiple Linear Regression In Python.mp4 | 100.8 MB |
| 85 - Loan-Log.ipynb | 127.3 KB |
| 85 - Practical Task 1.html | 1.0 KB |
| 86 - Practical Task 2.html | 1.1 KB |
| 87 - Practical Task 3.html | 3.3 KB |
| 88 - Comprehensive Interview Preparation Questions.html | 1.4 KB |
| Loan.ipynb | 213.0 KB |
| Loan.xlsx | 25.6 KB |
| Loan.xlsx - loan_data.csv | 19.8 KB |
| 10 - Exercise-1.pdf | 553.8 KB |
| 10 - Practice Exercise 1.html | 307 bytes |
| 11 - Measures Of Dispersion.mp4 | 14.4 MB |
| 12 - Exercise-2.pdf | 469.9 KB |
| 12 - Practice Exercise 2.html | 307 bytes |
| 13 - Installing Python And Anaconda.mp4 | 15.3 MB |
| 14 - Opening Jupyter Notebook.mp4 | 54.7 MB |
| 15 - Introduction To Jupyter.mp4 | 36.4 MB |
| 16 - Arithmetic Operators In Python Python Basics.mp4 | 10.5 MB |
| 17 - Strings In Python Python Basics.mp4 | 81.4 MB |
| 18 - Lists Part 1.mp4 | 11.3 MB |
| 19 - Lists Part 2.mp4 | 13.4 MB |
| 20 - Tuples And Dictionaries.mp4 | 13.0 MB |
| 21 - Working With Numpy Library Of Python.mp4 | 52.9 MB |
| 22 - Customer.csv | 64.0 KB |
| 22 - Working With Pandas Library Of Python.mp4 | 55.9 MB |
| 23 - Working With Seaborn Library Of Python.mp4 | 61.7 MB |
| 24 - Python File For Additional Practice.html | 307 bytes |
| 24 - Reference-Guide-for-Python-practice.ipynb | 80.2 KB |
| 25 - About The Upcoming Role Play.html | 1.1 KB |
| 26 - Gathering Business Knowledge.mp4 | 8.7 MB |
| 27 - Data Exploration.mp4 | 14.6 MB |
| 28 - House-Price.csv | 50.6 KB |
| 28 - The Dataset And The Data Dictionary.mp4 | 127.4 MB |
| 29 - Data Import In Python.mp4 | 35.5 MB |
| 29 - House-Price.csv | 50.6 KB |
| 30 - Movie-collection.csv | 55.8 KB |
| 30 - Project Exercise 1.html | 512 bytes |
| 31 - 03-04-PDE-Univariate-Analysis-Uni.pdf | 333.4 KB |
| 31 - Univariate Analysis And Edd.mp4 | 19.0 MB |
| 32 - Edd In Python.mp4 | 123.8 MB |
| 33 - Project Exercise 2.html | 204 bytes |
| 34 - 04-06-PDE-Outlier-Treatment.pdf | 355.1 KB |
| 34 - Outlier Treatment.mp4 | 16.2 MB |
| 35 - Outlier Treatment In Python.mp4 | 76.5 MB |
| 36 - Project Exercise 3.html | 204 bytes |
| 37 - 04-05-PDE-Missing-value.pdf | 315.7 KB |
| 37 - Missing Value Imputation.mp4 | 15.4 MB |
| 38 - Missing Value Imputation In Python.mp4 | 34.5 MB |
| 39 - Project Exercise 4.html | 204 bytes |
| 40 - 04-07-PDE-Seasonality.pdf | 364.1 KB |
| 40 - Seasonality In Data.mp4 | 12.3 MB |
| 41 - 04-07-Variable-Transformation.pdf | 456.1 KB |
| 41 - Variable Transformation.mp4 | 22.1 MB |
| 42 - Variable Transformation And Deletion In Python.mp4 | 39.9 MB |
| 43 - Project Exercise 5.html | 204 bytes |
| 44 - 04-11-Dummy-Var.pdf | 163.0 KB |
| 44 - Dummy Variable Creation Handling Qualitative Data.mp4 | 21.7 MB |
| 45 - Dummy Variable Creation In Python.mp4 | 43.7 MB |
| 46 - Project Exercise 6.html | 204 bytes |
| 47 - 01-INtro.pdf | 190.4 KB |
| 47 - Three Classifiers And The Problem Statement.mp4 | 31.8 MB |
| 48 - 02-whynot-linear.pdf | 155.3 KB |
| 48 - Why Cant We Use Linear Regression.mp4 | 28.0 MB |
| 49 - 03-logistic.pdf | 352.7 KB |
| 49 - Logistic Regression.mp4 | 55.0 MB |
| 50 - Training A Simple Logistic Model In Python.mp4 | 76.1 MB |
| 51 - Project Exercise 7.html | 307 bytes |
| 52 - 04-P-value.pdf | 228.0 KB |
| 52 - Result Of Simple Logistic Regression.mp4 | 44.3 MB |
| 53 - 05-Multiple-predictors.pdf | 151.3 KB |
| 53 - Logistic With Multiple Predictors.mp4 | 13.6 MB |
| 54 - Training Multiple Predictor Logistic Model In Python.mp4 | 40.9 MB |
| 55 - Project Exercise 8.html | 307 bytes |
| 56 - 06-Confusion-matrix.pdf | 222.3 KB |
| 56 - Confusion Matrix.mp4 | 40.1 MB |
| 57 - Creating Confusion Matrix In Python.mp4 | 75.4 MB |
| 58 - 08-ROC.pdf | 306.9 KB |
| 58 - Evaluating Performance Of Model.mp4 | 60.1 MB |
| 59 - Evaluating Model Performance In Python.mp4 | 14.4 MB |
| 60 - Project Exercise 9.html | 204 bytes |
| 61 - 07-LDA.pdf | 183.1 KB |
| 61 - Linear Discriminant Analysis.mp4 | 67.7 MB |
| 62 - Lda In Python.mp4 | 17.0 MB |
| 63 - Project Exercise 10.html | 204 bytes |
| 64 - 10-Test-Train.pdf | 238.7 KB |
| 64 - Testtrain Split.mp4 | 64.6 MB |
| 65 - More About Testtrain Split.html | 512 bytes |
| 66 - Testtrain Split In Python.mp4 | 52.4 MB |
| 67 - Project Exercise 11.html | 204 bytes |
| 6 - 01-01-Lecture-TypesOfData.pdf | 177.7 KB |
| 6 - Types Of Data.mp4 | 20.7 MB |
| 7 - 01-02-Lecture-TypesOfStatistics.pdf | 171.7 KB |
| 7 - Types Of Statistics.mp4 | 7.9 MB |
| 8 - 01-03-Lecture-DataSummaryandGraph.pdf | 317.9 KB |
| 8 - Describing Data Graphically.mp4 | 61.5 MB |
| 9 - 01-04-Lecture-Centers.pdf | 313.0 KB |
| 9 - Measures Of Centers.mp4 | 29.8 MB |
| 3 - Introduction To Machine Learning.mp4 | 145.6 MB |
| 3 - Lecture-machineLearning.pdf | 991.6 KB |
| 4 - This Is A Milestone.mp4 | 70.7 MB |
| 5 - Building A Machine Learning Model.mp4 | 27.7 MB |
| 89 - The Final Milestone.mp4 | 8.4 MB |
| 90 - About Your Certificate.html | 921 bytes |
| 91 - Bonus Lecture.html | 9.1 KB |
| OnlineFood.ipynb | 1.0 MB |
| onlinefoods.xlsx - onlinefoods.csv | 21.2 KB |
| Restaurant_revenue (1).csv | 88.3 KB |
| Resutrants.ipynb | 2.0 MB |
| 72 - 11-results.pdf | 170.9 KB |
| 72 - Understanding The Results Of Classification Models.mp4 | 67.0 MB |
| 73 - 12-steps.pdf | 148.1 KB |
| 73 - Summary Of The Three Models.mp4 | 35.6 MB |
| 74 - The Final Exercise.html | 1.8 KB |
| 74 - weekly.csv | 60.1 KB |
| 75 - New Ai Features In Python The Latest Updates You Must Know.html | 4.6 KB |
| 68 - 09-KNN.pdf | 236.7 KB |
| 68 - Knearest Neighbors Classifier.mp4 | 120.4 MB |
| 69 - Knearest Neighbors In Python Part 1.mp4 | 56.2 MB |
| 70 - Knearest Neighbors In Python Part 2.mp4 | 64.4 MB |
| 71 - Project Exercise 12.html | 204 bytes |
| 10_Test_Train.pdf | 238.7 KB |
| 11_results.pdf | 170.9 KB |
| 12_steps.pdf | 148.1 KB |
| Python_CrashC1.ipynb | 29.6 KB |
| Python_cc2.ipynb | 169.5 KB |
| Product.txt | 139.5 KB |
Name
DL
Uploader
Size
S/L
Added
-
102 bytes
[13
/
13]
2026-07-23
| Uploaded by anonymous | Size 102 bytes | Health [ 13 /13 ] | Added 2026-07-23 |
-
4.7 MB
[12
/
4]
2023-07-01
| Uploaded by FreeCourseWeb | Size 4.7 MB | Health [ 12 /4 ] | Added 2023-07-01 |
-
738.9 MB
[17
/
5]
2023-06-02
| Uploaded by tutsgalaxy | Size 738.9 MB | Health [ 17 /5 ] | Added 2023-06-02 |
-
150.6 MB
[0
/
1]
2023-06-02
| Uploaded by freecoursewb | Size 150.6 MB | Health [ 0 /1 ] | Added 2023-06-02 |
NOTE
SOURCE: Logistic Regression in Python
-----------------------------------------------------------------------------------
COVER
-----------------------------------------------------------------------------------
MEDIAINFO
None
×