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Autor Tópico: Forecasting Models and Time Series for Business in Python  (Lida 201 vezes)

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Offline mitsumi

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Forecasting Models and Time Series for Business in Python
« em: 17 de Junho de 2021, 10:55 »

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 123 lectures (8h 11m) | Size: 2.8 GB
Learn Holt-Winters, Arima, Sarimax, Tensorflow Time Series, Facebook Prophet, XGBoost for Demand Planning & Forecasting

What you'll learn:
Holt-Winters
TBATS
SARIMAX
Facebook Prophet
Tensorflow Structural Time Series
XGBoost
Time Series Analysis
Demand Planning and Forecasting

Requirements
Basic Statistics: Linear regression, p-value
Basic Python desirable

Description
Welcome to the most exciting online course about Forecasting Models in Python. I will show everything you need to know to understand the now and predict the future.

Forecasting is always sexy - knowing what will happen usually drops jaws and earns admiration. On top, it is fundamental in the business world. Companies always provide Revenue growth and EBIT estimates, which are based on forecasts. Who is doing them? Well, that could be you!

WHY SHOULD YOU ENROLL IN THIS COURSE?

YOU WILL LEARN THE INTUITION BEHIND THE MODELS WITHOUT FOCUSING TOO MUCH ON THE MATH

It is fundamental that you know why a model makes sense and the underlying assumptions behind it. I will explain to you each model using words, graphs, and metaphors, leaving math and the Greek alphabet to a minimum.

THOROUGH COURSE STRUCTURE OF MOST IMPACTFUL ECONOMETRIC TECHNIQUES

The techniques in this course are the ones I believe will be most impactful, up to date, and sought after:

Holt-Winters

TBATS

SARIMAX

TensorFlow Structural Time Series

Facebook Prophet

Facebook Prophet + XGBoost

Ensemble approach

WE CODE TOGETHER LINE BY LINE

I will guide you through every step of the way. I will also explain all parameters and functions that you need to use, step by step.

THE FINAL REASON IS THAT YOU PRACTICE, PRACTICE, PRACTICE.

For each algorithm, there is a challenge. This means that each technique has 2 case studies. The goal is that you apply immediately what you have learned. I give you a dataset and a list of actions you need to take to solve it. I think it is the best way to really cement all the techniques in you.

Did I spike your interest? Join me and learn how to predict the future!

Who this course is for
Professionals looking to learn about Demand Forecasting and Time Series


Download link:
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