Deep Dive into Time Series Forecasting Part 1 - Statistical Models
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Deep Dive into Time Series Forecasting
Part 1 - Statistical Models

  • Get started with Time Series forcasting principles and concepts with Statistical forecasting models.
  • Learn the math and implement them in Python using Statsmodels and learn to tune them.
  • Know the Do's and Don't and ideas to succeed in Industrial Forecasting projects.

Created by Selva Prabhakaran

  • 16 video lessons

  • English

What you will learn

01

Frame Data Science Problem Statement

02

Extensive Exploratory Data Analysis

03

Feature Engineering Strategies

04

Build Multiple Time Series Models

05

Model Evaluation and Improvement

06

Advanced Machine Learning Algorithms

07

Domain based data science strategies

08

Derive high business impact insights

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!

  • 4.5+Instructor rating

  • 200+ reviews

  • 10K+students

  • 15+ Courses

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