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Deep Dive into Multi Time Series Forecasting
- Vector Auto Regression

  • Dive in deeper to study the VAR used in Time Series Forecasting with their application in real world.

Created by Selva Prabhakaran

  • 26 video lessons

  • English

What you will learn

01

Understanding the VAR Model formula

02

How to check the bi-directional relationship using Granger Causality

03

Procedure to building a VAR model in Python correctly

04

Interpreting the results of VAR model

05

Deeper Understanding of VARMA and VARMAX

06

Strategy to find best VAR model

07

Strategy to Hyperparameter tuning like Auto ARIMA

08

How to introduce Exogenous variable into VARMAX Forecast

Course Curriculum

Requirements

  • Courses Page1 Basics of Python
  • Courses Page1 Foundational knowledge of Data Science
  • Courses Page1 High school maths

Who should attend this course?

  • Data Science Aspirants

  • Data Science Professionals

  • Software/Data engineers interested in quantitative analysis

  • Professionals working with large datasets

  • Data analysts, economists, researchers

About the course

You will learn the following skills by the end of the course:

  • LightGBM
  • XGBoost Random
  • Forest Decision Tree
  • Logistic Regression
  • Hyperparameter
  • Tuning Feature Importance Confusion Matrix
  • ROC AUC
  • Concordance and Discordance
  • Precision Recall Curve
  • Capture Rates and Gains
  • Feature Engineering
  • Label Encoding
  • Frequency Encoding
  • Chi-Square test ANOVA test
  • Exploratory Data Analysis
  • Memory
  • Optimization
  • Data Preprocessing

Instructor

Selva Prabhakaran Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this project!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I’ve deployed 20+ global products. I’m also the Founder & Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I’ve put up the series of courses and projects with detailed explanations – just like an on the job experience. Hope you love it!

  • 4.8+Instructor rating

  • 200+ reviews

  • 50K+students

  • 33+ Courses

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