https://github.com/vaibhavs10/stats101

Code and high level information to get started with Statistics and Math required for Machine Learning
https://github.com/vaibhavs10/stats101

Last synced: 17 days ago
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Code and high level information to get started with Statistics and Math required for Machine Learning

• Host: GitHub
• URL: https://github.com/vaibhavs10/stats101
• Owner: Vaibhavs10
• Created: 2018-07-07T10:29:49.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-07-07T13:15:17.000Z (over 6 years ago)
• Last Synced: 2023-08-26T05:22:53.515Z (over 1 year ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 9.27 MB
• Stars: 0
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Statistics 101 (Hacker Way)

*Statistics*/ *Mathematics* is the backbone of Data Science and serves as an important tool (accelerator) during your client engagements.

This course covers (below) the basics required to foray into Data Science and build Data-Driven products.

***Math Concepts***

1. Basic Metrics: Mean, Variance, Covariance, Correlation

2. Discrete Probability Distributions: Bernoulli, Binomial

3. Cumulative Mass Function, Probability Mass Function

4. Continuous Probability Distributions: Poisson, Uniform, Normal, Beta, Gamma

5. Cumulative Distribution Function, Probability Density Function

***ML Applications***

1. Direct Simulation

2. Shuffling

3. Bootstrapping

4. Application to A/B Testing