Udemy - Forecasting Sales With Time Series, Lightgbm and Random F...

  • Category Other
  • Type Tutorials
  • Language English
  • Total size 1.5 GB
  • Uploaded By freecoursewb
  • Downloads 156
  • Last checked 3 days ago
  • Date uploaded 1 year ago
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Infohash : 97C490AC7C9CAD884505A13744FF87DE7B06B919



Forecasting Sales With Time Series, Lightgbm & Random Forest

https://DevCourseWeb.com

Published 2/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.52 GB | Duration: 3h 1m

Learn how to build sales forecasting models using Time Series, ARIMA, SARIMA, LightGBM, Random Forest, and LSTM

What you'll learn
Learn how to build sales forecasting model using ARIMA, SARIMA, LightGBM, Random Forest, and LSTM
Learn how to conduct customer segmentation analysis
Learn how to analyze sales performance trend
Learn how to evaluate forecasting model’s accuracy and performance by calculating mean absolute error and conduct residual analysis
Learn how time series forecasting model work. This section will cover data collection, preprocessing, train test split, model selection, and model training
Learn about factors that can contribute to sales performance, such as seasonal trends, market saturation and supply chain efficiency
Learn how to find and download datasets from Kaggle
Learn how to clean dataset by removing missing rows and duplicate values
Learn how to analyze order fulfilment efficiency
Learn the basic fundamentals of sales forecasting

Requirements
No previous experience in sales forecasting is required
Basic knowledge in Python and statistics

Files:

[ DevCourseWeb.com ] Udemy - Forecasting Sales With Time Series, Lightgbm and Random Forest
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 1 - Introduction
    • 1 - Introduction to the Course.mp4 (63.0 MB)
    • 2 - Forecasting-Sales-with-Time-Series.pptx (1.3 MB)
    • 2 - Table of Contents.mp4 (26.4 MB)
    • 3 - Whom This Course is Intended for.mp4 (17.9 MB)
    10 - Customer Segmentation Analysis
    • 13 - Customer Segmentation Analysis.mp4 (105.8 MB)
    11 - Analyzing Order Fulfilment Efficiency
    • 14 - Analyzing Order Fulfilment Efficiency.mp4 (60.6 MB)
    12 - Analyzing Sales Performance Trend
    • 15 - Analyzing Sales Performance Trend.mp4 (90.3 MB)
    13 - Forecasting Sales with ARIMA
    • 16 - Forecasting Sales with ARIMA.mp4 (140.5 MB)
    14 - Forecasting Sales with SARIMA
    • 17 - Forecasting Sales with SARIMA.mp4 (80.9 MB)
    15 - Forecasting Sales with LightGBM
    • 18 - Forecasting Sales with LightGBM.mp4 (192.6 MB)
    16 - Forecasting Sales with Random Forest
    • 19 - Forecasting Sales with Random Forest.mp4 (58.2 MB)
    17 - Forecasting Sales with LSTM
    • 20 - Forecasting Sales with LSTM.mp4 (180.9 MB)
    18 - Calculating Mean Absolute Error Conducting Residual Analysis
    • 21 - Calculating Mean Absolute Error Conducting Residual Analysis.mp4 (47.2 MB)
    19 - Conclusion Summary
    • 22 - Conclusion Summary.mp4 (25.7 MB)
    2 - Tools IDE and Datasets
    • 4 - Tools IDE and Datasets.mp4 (135.4 MB)
    3 - Introduction to Sales Forecasting
    • 5 - Introduction to Sales Forecasting.mp4 (19.4 MB)
    4 - How Time Series Forecasting Model Works
    • 6 - How Time Series Forecasting Model Works.mp4 (117.5 MB)
    5 - Factors That Can Contribute to Sales Performance
    • 7 - Factors That Can Contribute to Sales Performance.mp4 (22.9 MB)
    6 - Setting Up Google Colab IDE
    • 8 - Google Colab IDE.txt (0.0 KB)
    • 8 - Setting Up Google Colab IDE.mp4 (30.8 MB)
    7 - Finding Downloading Sales Report Dataset From Kaggle
    • 9 - Finding Downloading Sales Report Dataset From Kaggle.mp4 (52.3 MB)
    • 9 - Kaggle.txt (0.0 KB)
    8 - Project Preparation
    • 10 - Uploading Sales Report Dataset to Google Colab.mp4 (8.1 MB)
    • 10 - train.csv (2.0 MB)
    • 11 - Quick Overview of Sales Report Dataset.mp4 (52.9 MB)
    9 - Cleaning Dataset by Removing Missing Values Duplicates
    • 12 - Cleaning Dataset by Removing Missing Values Duplicates.mp4 (20.2 MB)
    • Bonus Resources.txt (0.4 KB)

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