Description

High Performance Time Series

High Performance Time Series

Become the time-series domain expert for your organization

Become the Time Series Expert
for your organization

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The High-Performance Time Series Forecasting Course is an amazing course designed to teach Business Analysts and Data Scientists how to reduce forecast error using state-of-the-art forecasting techniques that have won competitions. You’ll undergo a complete transformation learning the most in-demand skills that organizations need right now. Time to accelerate your career.

Crafted For Business Analysts & Data Scientists

That need to reduce forecasting error and scale results for your organization.

This is possibly my most challenging course ever. You’ll learn the time series skills that have taken me 10-years of study, practice, and experimentation.

This course gives you the tools you need to meet today’s forecasting demands.

A full year was spent on building two of the software packages you’ll learn, modeltime and timetk.

Plus, I’m teaching you GluonTS, a state-of-the-art deep learning framework for time series written in python.

This course will challenge you. It will change you. It did me.

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– Matt Dancho, Course Instructor & Founder of Business Science

Undergo a Complete Transformation
By learning forecasting techniques that get results

With High-Performance Forecasting, you will undergo a complete transformation by learning the most in-demand skills for creating high-accuracy forecasts.

Through this course, you will learn and apply:

• Machine Learning & Deep Learning
• Feature Engineering
• Visualization & Data Wrangling
• Transformations
• Hyper Parameter Tuning
• Forecasting at Scale (Time Series Groups)

Part 1

Time Series Feature Engineering

First, we build your time series feature engineering skills. You learn:

• Visualization: Identifying features visually using the most effective plotting techniques
• Data Wrangling: Aggregating, padding, cleaning, and extending time series data
• Transformations: Rolling, Lagging, Differencing, Creating Fourier Series, and more
• Feature Engineering: Over 3-hours of content on introductory and advanced feature engineering

Part 2

Machine Learning for Time Series

Next, we build your time series machine learning skills. You learn:

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• 17 Algorithms: 8 hours of content on 17 TOP Algorithms. Divided into 5 groups:
  • ARIMA
  • Prophet
  • Exponential Smoothing – ETS, TBATS, Seasonal Decomposition
  • Machine Learning – Elastic Net, MARS, SVM, KNN, Random Forest, XGBOOST, Cubist, NNET & NNETAR
  • Boosted Algorithms – Prophet Boost & ARIMA Boost
• Hyper Parameter Tuning: Strategies to reduce overfitting & increase model performance
• Time Series Groups: Scale your analysis from one time series to hundreds
• Parallel Processing: Needed to speed up hyper parameter tuning and forecasting at scale
• Ensembling: Combining many algorithms into a single super learner

Part 3

Deep Learning for Time Series

Next, we build your time series deep learning skills. You learn:

• GluonTS: A state-of-the-art forecasting package that’s built on top of mxnet (made by Amazon)
• Algorithms: Learn DeepAR, DeepVAR, NBEATS, and more!

Challenges & Cheat Sheets

Next, we build your time series machine learning skills. You learn:

• Cheat Sheets: Developed to make your forecasting workflow reproducible on any problem
• Challenges: Designed to test your abilities & solidify your knowledge

Summary of what you get

• A methodical training plan that goes from concept to production ($10,000 value)
  • Part 1 – Feature Engineering with Timetk
  • Part 2 – Machine Learning with Modeltime
  • Part 3 – Deep Learning with GluonTS
  • Challenges & Cheat Sheets

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