GithubHelp home page GithubHelp logo

komal11lamba / 50-days-of-statistics-for-data-science Goto Github PK

View Code? Open in Web Editor NEW
25.0 1.0 8.0 1016 KB

This repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.

Jupyter Notebook 100.00%
statistics python feature-engineering feature-extraction feature-selection feature-scaling dimensionality-reduction eda

50-days-of-statistics-for-data-science's Introduction

50-days-of-Statistics-for-Data-Science

This repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.

Sr No Notebook Topic Colab
1 Elements of Structured Data Open In Colab
2 Rectangular Data Open In Colab
3 Estimates of Location Open In Colab
4 Estimates of Variability Open In Colab
5 Exploring the Data Distribution Open In Colab
6 Exploring Binary and Categorical Data Open In Colab
7 Correlation Open In Colab
8 Exploring Two or More Variables Open In Colab
9 Random Sampling and Sample Bias Open In Colab
10 Selection Bias Open In Colab
11 Sampling Distribution of a Statistic Open In Colab
12 The Bootstrap Open In Colab
13 Confidence Intervals Open In Colab
14 Normal Distribution Open In Colab
15 Long-Tailed Distributions Open In Colab
16 Student’s t-Distribution Open In Colab
17 Binomial Distribution Open In Colab
18 Chi-Square Distribution Open In Colab
19 F-Distribution Open In Colab
20 Poisson and Related Distributions Open In Colab
21 A/B Testing Open In Colab
22 Hypothesis Tests Open In Colab
23 Resampling Open In Colab
24 Statistical Significance and p-Values Open In Colab
25 t-Tests Open In Colab
26 Multiple Testing Open In Colab
27 Degrees of Freedom Open In Colab
28 ANOVA Open In Colab
29 Chi-Square Test Open In Colab
30 Multi-Arm Bandit Algorithm Open In Colab
31 Power and Sample Size Open In Colab
32 Simple Linear Regression Open In Colab
33 Multiple Linear Regression Open In Colab
34 Prediction Using Regression Open In Colab
35 Factor Variables in Regression Open In Colab
36 Interpreting the Regression Equation Open In Colab
37 Regression Diagnostics Open In Colab
38 Polynomial and Spline Regression Open In Colab
39 Naïve Bayes Open In Colab
40 Discriminant Analysis Open In Colab
41 Logistic Regression Open In Colab
42 Evaluating Classification Models Open In Colab
43 Strategies for Imbalanced Data Open In Colab
44 K-Nearest Neighbors Open In Colab
45 Tree Models Open In Colab
46 Bagging and the Random Forest Open In Colab
47 Boosting Open In Colab
48 Principal Components Analysis Open In Colab
49 K-Means Clustering Open In Colab
50 Hierarchical Clustering Open In Colab
51 Model-Based Clustering Open In Colab
52 Scaling and Categorical Variables Open In Colab

50-days-of-statistics-for-data-science's People

Contributors

komal11lamba avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar

50-days-of-statistics-for-data-science's Issues

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.