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Time Series Forecasting with Python

via Zero To Mastery

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Details

Provider

Zero To Mastery
Pricing

Paid Course
Languages

English
Certificate

Paid Certificate Available
Duration & workload

10 hours
Sessions

On-Demand

Found in

Overview

This project-based course will put you in the role of a Business Data Analyst at Airbnb tasked with predicting demand for Airbnb property bookings in New York. To accomplish this goal, you'll use the Python programming language to build a powerful tool that utilizes the magic of time series forecasting.

How to utilize the power of time series forecasting to predict the future
How to use the four most relevant forecasting models used by Business Data Analysts today
Practice the day-to-day skills needed for Business Data Analysis
Build an impressive project to add to your portfolio to help you get hired
Enhance your proficiency with Python, one of the most popular programming languages

Syllabus

Introduction

Course Introduction
Exercise: Meet Your Classmates and Instructor
Course Material
Why Forecasting Matters
Understanding Your Video Player (notes, video speed, subtitles + more)
Set Your Learning Streak Goal

Exploratory Data Analysis

Game Plan
TIme Series Data
Case Study Briefing
Python - Directory and Libraries
Python - Loading the Data
Python - Renaming Variable
Python - Summary Statistics
Additive vs. Multiplicative Seasonality
Python - Seasonal Decomposition
Python - Seasonal Graphs
Python - Visualization - Basic Plot
Python - Visualization - Customization
Python - Visualization -Adding Events
Python - Correlation
Auto-Correlation Plots
Python - Auto-Correlation Plot
Python - Useful Commands Template
Let's Have Some Fun (+ Free Resources)

(Facebook) Prophet

Game Plan for Prophet
Prophet and Structural Time Series
Python - Preparing the Script
Python - Prepare Date Variable
Python - Easter Holiday
Python - Remaining Holidays
Python - Wrapping up the Events
Prophet Parameters
Python - Prophet Model
Cross-Validation
Python - Cross-Validation
Assessing Forecasting
Python - Cross-Validation Performance and Plotting
Parameter Tuning
Python - Parameter Grid
Python - Parameter Tuning
Python - Best Parameters and Exporting
Python - Updating Useful Commands (Part 1)
Python - Preparing Data Sets
Python - Parameters and Final Model
Python - Forecasting
Python - Exporting Forecasts
Python - Updating Useful Commands (Part 2)
Pros and Cons
Unlimited Updates

SARIMAX

SARIMAX Game Plan
ARIMA
Python - Preparing Script
Auto-Regressive
Integrated
Python - Stationarity and Differencing
Moving Average Component
Optimization Factors
Python - SARIMAX Model
Python - Cross-Validation
Python - Parameter Grid
Python - Parameter Tuning
Python - Exporting Best Parameters
Python - Preparing the Script
Python - Preparing Data
Python - Tuned SARIMAX Model
Python - Forecasting
Python - Visualization and Export
SARIMAX Pros and Cons
Course Check-In

How LinkedIn Silverkite Works

Recurrent Neural Networks (RNN) Long Short-Term Memory (LSTM)

Game Plan for LSTM
Simple Neural Network
Recurrent Neural Networks (RNN)
Long Short-Term Memory (LSTM)
Python - Directory and Libraries
Python - Time Series Objects
Python - Time Variables
Python - Scaling
LSTM Parameters
Activation Functions
Python - LSTM Model
Python - Cross-Validation
Python - Cross-Validation Performance
Python - Parameter Grid
Python - Parameter Tuning (Round 1)
Python - Parameter Tuning (Round 2)
Python - Changing from CPU to GPU
Python - Parameter Tuning (Final Results)
Python - Preparing Script
Python - Tuned LSTM Model
Python - Predictions and Exporting
Pros and Cons

Ensemble

Ensemble Game Plan
Ensemble Mechanism
Python - Preparing Script and Loading Predictions
Python - Loading Errors
Python - Forecasting Weights
Python - Ensemble Forecast and Visualization
Ensemble Pros and Cons

Where To Go From Here?

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LinkedIn Endorsements

Taught by

Diogo Resende

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