Deep Dive into Time Series - Singular Spectrum Analysis
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Deep Dive into Time Series Forecasting -
Singular Spectrum Analysis

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

Created by Selva Prabhakaran

  • 18 video lessons

  • English

What you will learn

01

Performing Singular spectrum analysis in Python

02

SSA - Math and interpretation of results

03

Building useful SSA features for Forecasting

04

Hands-on code
walkthrough

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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