Python Regression Analysis: Statistics & Machine Learning

سرفصل های دوره

Learn Complete Hands-On Regression Analysis for Practical Statistical Modelling and Machine Learning in Python

1 - INTRODUCTION TO THE COURSE The Key Concepts and Software Tools

1 - Welcome to the Course

2 - Data and Scripts For the Course.html

2 - scriptsLecture.zip

3 - Python Data Science Environment

4 - For Mac Users

5 - Introduction to IPython

6 - IPython in Browser

7 - Python Data Science Packages To Be Used

2 - Read in Data From Different Sources With Pandas

8 - What are Pandas

9 - Read in Data from CSV

10 - Read in Excel Data

11 - Read in HTML Data

3 - Data Cleaning & Munging

12 - Remove Missing Values

13 - Conditional Data Selection

14 - Data Grouping

15 - Data Subsetting

16 - Ranking & Sorting

17 - Concatenate

18 - Merging & Joining Data Frames

4 - Statistical Data AnalysisBasic

19 - What is Statistical Data Analysis

20 - Some Pointers on Collecting Data for Statistical Studies

21 - Some Pointers on Exploring Quantitative Data.html

22 - Explore the Quantitative Data Descriptive Statistics

23 - Grouping & Summarizing Data by Categories

24 - Visualize Descriptive StatisticsBoxplots

25 - Common Terms Relating to Descriptive Statistics

26 - Data Distribution Normal Distribution

27 - Check for Normal Distribution

28 - Standard Normal Distribution and Zscores

29 - Confidence IntervalTheory

30 - Confidence IntervalCalculation

5 - Regression Modelling for Defining Relationship bw Variables

31 - Explore the Relationship Between Two Quantitative Variables

32 - Correlation Analysis

33 - Linear RegressionTheory

34 - Linear RegressionImplementation in Python

35 - Conditions of Linear Regression

36 - Conditions of Linear RegressionCheck in Python

37 - Polynomial Regression

38 - GLM Generalized Linear Model

39 - Logistic Regression

6 - Machine Learning for Data Science

40 - How is Machine Learning Different from Statistical Data Analysis

41 - What is Machine Learning ML About Some Theoretical Pointers

7 - Machine Learning Based Regression Modelling

42 - What Is This Section About

43 - Data Preparation for Supervised Learning

44 - Pointers on Evaluating the Accuracy of Classification and Regression Modelling

45 - RFRegression

46 - Support Vector Regression

47 - knnRegression

48 - Gradient Boostingregression

49 - Theory Behind ANN and DNN

50 - Regression with MLP

8 - Miscallaneous Information

51 - Using Colabs for Online Data Science

51 - colab.zip

52 - Colab GPU

53 - Github

54 - What is Machine Learning

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تولید کننده: Udemy-Training