Build a Time Series Crate in Rust and Publish to Cargo

سرفصل های دوره

Learn to build an open-source time-series library in Rust from scratch.

1 - Introduction

1 -Getting Started with Codebase

1 - Introduction.html

1 - Open Source Development Requirements (Must Read).html

2 - Autocorrelation

1 -Math and Code Implementation Autocorrelation Module

3 - Stationarity

1 -Math and Code Implementation Stationarity Module

4 - Linear Regression - Trend Detection

1 -Math behind Linear Regression for Identifying Trend Patterns

2 -Conversion of Linear Regression Math to Code

5 - Seasonality - Differencing Method

1 -Seasonality Detection using Differencing Technique

6 - White Noise

1 -Mathematical Intuition and Code Implementation

7 - Autoregressive Model

1 -Math behind Autoregressive model

2 -Building the Autoregressive Model from Scratch

8 - Moving Average

1 -Math behind Moving Average

2 -Code Moving Average Module

3 -Math behind Weighted Moving Average

4 -Code Weighted Moving Average Module

9 - ARMA Model - Autoregressive Moving Average

1 -Math behind ARMA Model

2 -Build ARMA Model from Scratch

10 - ARIMA Model - Autoregressive Integrated Moving Average

1 -Math behind Autoregressive Integrated Moving Average

2 -Build ARIMA Model From Scratch

11 - SARIMA Model - Seasonal Autoregressive Integrated Moving Average

1 -Math behind SARIMA model

2 -Build SARIMA Model From Scratch

12 - Exponential Smoothing

1 -Math Behind Single Exponential Smoothing

2 -Build Single Exponential Smoothing Model From Scratch

3 -Math Behind Holts Linear Trend Model

4 -Build Holts Linear Trend Model From Scratch

13 - Publish as a Library to Crate Registry

1 -Publish to Github repo and Export the Cargo Project

2 -Cargo Package Testing

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تولید کننده: Udemy