Logistic Regression in Python

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size3 GB
  • Uploaded Byfreecoursewb
  • Downloads78
  • Last checkedJul. 24th '26
  • Date uploadedJul. 23rd '26
  • Seeders 0
  • Leechers42

Infohash : B78B34440BBB1EB48BAB857AD689B8AF827C606C

Logistic Regression in Python

https://WebToolTip.com

Last updated 3/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.04 GB | Duration: 7h 40m

Logistic regression in Python tutorial for beginners. You can do Predictive modeling using Python after this course.

What you'll learn
Understand how to interpret the result of Logistic Regression model in Python and translate them into actionable insight
Learn the linear discriminant analysis and K-Nearest Neighbors technique in Python
Preliminary analysis of data using Univariate analysis before running classification model
Predict future outcomes basis past data by implementing Machine Learning algorithm
Indepth knowledge of data collection and data preprocessing for Machine Learning logistic regression problem
Learn how to solve real life problem using the different classification techniques
Course contains a end-to-end DIY project to implement your learnings from the lectures
Basic statistics using Numpy library in Python
Data representation using Seaborn library in Python
Classification techniques of Machine Learning using Scikit Learn and Statsmodel libraries of Python

Requirements
Students will need to install Python and Anaconda software but we have a separate lecture to help you install the same

Files:

[ WebToolTip.com ] Logistic Regression in Python
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1 - Introduction
    • 1 - 00-Introduction-01-py.pdf (472.2 KB)
    • 1 - Welcome To The Course.mp4 (25.3 MB)
    • 2 - Course Resources.html (0.1 KB)
      • Logistic Regression in Python Data Files
      • Customer.csv (64.0 KB)
      • House-Price.csv (50.6 KB)
      • Product.txt (139.5 KB)
      Others
      • Classification.ipynb (171.7 KB)
      • Python_CrashC1.ipynb (29.6 KB)
      • Python_cc2.ipynb (169.5 KB)
      Presentation
      • 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)
      • 10_Test_Train.pdf (238.7 KB)
      • 11_results.pdf (170.9 KB)
      • 12_steps.pdf (148.1 KB)
      10 - Knearest Neighbors Classifier
      • 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 (0.2 KB)
      11 - Understanding The Results
      • 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)
      12 - Appendix 1 Linear Regression In Python
      • 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)
        • ML Practical task 3
        • Restaurant_revenue (1).csv (88.3 KB)
        • Resutrants.ipynb (2.0 MB)
        ML Task 1
        • Loan.ipynb (213.0 KB)
        • Loan.xlsx (25.6 KB)
        • Loan.xlsx - loan_data.csv (19.8 KB)
        ML Task 2
        • OnlineFood.ipynb (1.0 MB)
        • onlinefoods.xlsx - onlinefoods.csv (21.2 KB)
        13 - Congratulations About Your Certificate
        • 89 - The Final Milestone.mp4 (8.4 MB)
        • 90 - About Your Certificate.html (0.9 KB)
        • 91 - Bonus Lecture.html (9.1 KB)
        2 - Introduction To Machine Learning
        • 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)
        3 - Basics Of Statistics
        • 10 - Exercise-1.pdf (553.8 KB)
        • 10 - Practice Exercise 1.html (0.3 KB)
        • 11 - Measures Of Dispersion.mp4 (14.4 MB)
        • 12 - Exercise-2.pdf (469.9 KB)
        • 12 - Practice Exercise 2.html (0.3 KB)
        • 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)
        4 - Setting Up Python And Jupyter Notebook
        • 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)
        5 - Important Python Libraries
        • 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 (0.3 KB)
        • 24 - Reference-Guide-for-Python-practice.ipynb (80.2 KB)
        • 25 - About The Upcoming Role Play.html (1.1 KB)
        6 - Data Preprocessing
        • 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 (0.5 KB)
        • 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)

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