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Logistic Regression in Python

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Category Other
Added Thursday 23rd July 2026 03:06:26 AM (3 months ago)
Size102 bytes
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Torrent Files (151)
FilenameSize
Bonus Resources.txt102 bytes
Get Bonus Downloads Here.url204 bytes
1 - 00-Introduction-01-py.pdf472.2 KB
1 - Welcome To The Course.mp425.3 MB
2 - Course Resources.html102 bytes
Customer.csv64.0 KB
House-Price.csv50.6 KB
Classification.ipynb171.7 KB
02_whynot_linear.pdf155.3 KB
03_logistic.pdf352.7 KB
04_.pdf165.3 KB
04_P_value.pdf228.0 KB
05_Multiple_predictors.pdf151.3 KB
06_Confusion matrix.pdf222.3 KB
07_LDA.pdf183.1 KB
08_ROC.pdf306.9 KB
09_KNN.pdf236.7 KB
76 - The Problem Statement.mp414.2 MB
77 - Basic Equations And Ordinary Least Squares Ols Method.mp465.1 MB
78 - Assessing Accuracy Of Predicted Coefficients.mp4139.8 MB
79 - Assessing Model Accuracy Rse And R Squared.mp466.6 MB
80 - Simple Linear Regression In Python.mp489.7 MB
81 - Multiple Linear Regression.mp452.4 MB
82 - The F Statistic.mp486.7 MB
83 - Interpreting Results Of Categorical Variables.mp433.6 MB
84 - Multiple Linear Regression In Python.mp4100.8 MB
85 - Loan-Log.ipynb127.3 KB
85 - Practical Task 1.html1.0 KB
86 - Practical Task 2.html1.1 KB
87 - Practical Task 3.html3.3 KB
88 - Comprehensive Interview Preparation Questions.html1.4 KB
Loan.ipynb213.0 KB
Loan.xlsx25.6 KB
Loan.xlsx - loan_data.csv19.8 KB
10 - Exercise-1.pdf553.8 KB
10 - Practice Exercise 1.html307 bytes
11 - Measures Of Dispersion.mp414.4 MB
12 - Exercise-2.pdf469.9 KB
12 - Practice Exercise 2.html307 bytes
13 - Installing Python And Anaconda.mp415.3 MB
14 - Opening Jupyter Notebook.mp454.7 MB
15 - Introduction To Jupyter.mp436.4 MB
16 - Arithmetic Operators In Python Python Basics.mp410.5 MB
17 - Strings In Python Python Basics.mp481.4 MB
18 - Lists Part 1.mp411.3 MB
19 - Lists Part 2.mp413.4 MB
20 - Tuples And Dictionaries.mp413.0 MB
21 - Working With Numpy Library Of Python.mp452.9 MB
22 - Customer.csv64.0 KB
22 - Working With Pandas Library Of Python.mp455.9 MB
23 - Working With Seaborn Library Of Python.mp461.7 MB
24 - Python File For Additional Practice.html307 bytes
24 - Reference-Guide-for-Python-practice.ipynb80.2 KB
25 - About The Upcoming Role Play.html1.1 KB
26 - Gathering Business Knowledge.mp48.7 MB
27 - Data Exploration.mp414.6 MB
28 - House-Price.csv50.6 KB
28 - The Dataset And The Data Dictionary.mp4127.4 MB
29 - Data Import In Python.mp435.5 MB
29 - House-Price.csv50.6 KB
30 - Movie-collection.csv55.8 KB
30 - Project Exercise 1.html512 bytes
31 - 03-04-PDE-Univariate-Analysis-Uni.pdf333.4 KB
31 - Univariate Analysis And Edd.mp419.0 MB
32 - Edd In Python.mp4123.8 MB
33 - Project Exercise 2.html204 bytes
34 - 04-06-PDE-Outlier-Treatment.pdf355.1 KB
34 - Outlier Treatment.mp416.2 MB
35 - Outlier Treatment In Python.mp476.5 MB
36 - Project Exercise 3.html204 bytes
37 - 04-05-PDE-Missing-value.pdf315.7 KB
37 - Missing Value Imputation.mp415.4 MB
38 - Missing Value Imputation In Python.mp434.5 MB
39 - Project Exercise 4.html204 bytes
40 - 04-07-PDE-Seasonality.pdf364.1 KB
40 - Seasonality In Data.mp412.3 MB
41 - 04-07-Variable-Transformation.pdf456.1 KB
41 - Variable Transformation.mp422.1 MB
42 - Variable Transformation And Deletion In Python.mp439.9 MB
43 - Project Exercise 5.html204 bytes
44 - 04-11-Dummy-Var.pdf163.0 KB
44 - Dummy Variable Creation Handling Qualitative Data.mp421.7 MB
45 - Dummy Variable Creation In Python.mp443.7 MB
46 - Project Exercise 6.html204 bytes
47 - 01-INtro.pdf190.4 KB
47 - Three Classifiers And The Problem Statement.mp431.8 MB
48 - 02-whynot-linear.pdf155.3 KB
48 - Why Cant We Use Linear Regression.mp428.0 MB
49 - 03-logistic.pdf352.7 KB
49 - Logistic Regression.mp455.0 MB
50 - Training A Simple Logistic Model In Python.mp476.1 MB
51 - Project Exercise 7.html307 bytes
52 - 04-P-value.pdf228.0 KB
52 - Result Of Simple Logistic Regression.mp444.3 MB
53 - 05-Multiple-predictors.pdf151.3 KB
53 - Logistic With Multiple Predictors.mp413.6 MB
54 - Training Multiple Predictor Logistic Model In Python.mp440.9 MB
55 - Project Exercise 8.html307 bytes
56 - 06-Confusion-matrix.pdf222.3 KB
56 - Confusion Matrix.mp440.1 MB
57 - Creating Confusion Matrix In Python.mp475.4 MB
58 - 08-ROC.pdf306.9 KB
58 - Evaluating Performance Of Model.mp460.1 MB
59 - Evaluating Model Performance In Python.mp414.4 MB
60 - Project Exercise 9.html204 bytes
61 - 07-LDA.pdf183.1 KB
61 - Linear Discriminant Analysis.mp467.7 MB
62 - Lda In Python.mp417.0 MB
63 - Project Exercise 10.html204 bytes
64 - 10-Test-Train.pdf238.7 KB
64 - Testtrain Split.mp464.6 MB
65 - More About Testtrain Split.html512 bytes
66 - Testtrain Split In Python.mp452.4 MB
67 - Project Exercise 11.html204 bytes
6 - 01-01-Lecture-TypesOfData.pdf177.7 KB
6 - Types Of Data.mp420.7 MB
7 - 01-02-Lecture-TypesOfStatistics.pdf171.7 KB
7 - Types Of Statistics.mp47.9 MB
8 - 01-03-Lecture-DataSummaryandGraph.pdf317.9 KB
8 - Describing Data Graphically.mp461.5 MB
9 - 01-04-Lecture-Centers.pdf313.0 KB
9 - Measures Of Centers.mp429.8 MB
3 - Introduction To Machine Learning.mp4145.6 MB
3 - Lecture-machineLearning.pdf991.6 KB
4 - This Is A Milestone.mp470.7 MB
5 - Building A Machine Learning Model.mp427.7 MB
89 - The Final Milestone.mp48.4 MB
90 - About Your Certificate.html921 bytes
91 - Bonus Lecture.html9.1 KB
OnlineFood.ipynb1.0 MB
onlinefoods.xlsx - onlinefoods.csv21.2 KB
Restaurant_revenue (1).csv88.3 KB
Resutrants.ipynb2.0 MB
72 - 11-results.pdf170.9 KB
72 - Understanding The Results Of Classification Models.mp467.0 MB
73 - 12-steps.pdf148.1 KB
73 - Summary Of The Three Models.mp435.6 MB
74 - The Final Exercise.html1.8 KB
74 - weekly.csv60.1 KB
75 - New Ai Features In Python The Latest Updates You Must Know.html4.6 KB
68 - 09-KNN.pdf236.7 KB
68 - Knearest Neighbors Classifier.mp4120.4 MB
69 - Knearest Neighbors In Python Part 1.mp456.2 MB
70 - Knearest Neighbors In Python Part 2.mp464.4 MB
71 - Project Exercise 12.html204 bytes
10_Test_Train.pdf238.7 KB
11_results.pdf170.9 KB
12_steps.pdf148.1 KB
Python_CrashC1.ipynb29.6 KB
Python_cc2.ipynb169.5 KB
Product.txt139.5 KB
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