Скачать или смотреть Predicting Sales with TensorFlow Multivariate Regression for Supply Chain AI!

Hi Everyone,

📊 Learn Multivariate Regression with TensorFlow for Sales Prediction!

In this tutorial, we demonstrate how to predict product sales using multiple features like price and advertising spend. This project introduces a powerful application of TensorFlow in supply chain management and marketing analytics.

By understanding the relationship between features and sales, businesses can optimize pricing, allocate marketing budgets effectively, and forecast revenue with greater accuracy. This project is a perfect stepping stone for beginners and professionals exploring AI-driven forecasting. 🚀


What’s Covered in This Video?
1️⃣ Simulating Sales Data:

Generate a dataset with two features: Price and Advertising Spend.
Simulate realistic sales data based on these features with added noise for variability.
2️⃣ Building a Neural Network with TensorFlow:

Create a neural network with two hidden layers to handle multiple input features.
Use the Adam optimizer and MSE loss function to train the model.
3️⃣ Training and Testing:

Train the model on historical data, then evaluate its performance on test data.
Learn how to normalize data for better neural network performance.
4️⃣ Visualization:

Generate a scatter plot comparing predicted sales with actual sales.
See how the model performs against real-world-like data.

Graph Visualization:
This project generates a scatter plot showing:

Predicted Sales (Blue points): Model predictions on test data.
Actual Sales: Real sales values for comparison.
Diagonal Line (Red): Perfect predictions where predicted = actual.
Why Use TensorFlow for Sales Prediction?
TensorFlow makes it easy to build and train regression models that can:

Optimize Pricing: Understand how price affects sales to maximize revenue.
Improve Marketing Efficiency: Allocate budgets for advertising spend based on ROI predictions.
Support Decision-Making: Forecast future sales for better inventory and supply chain planning.
This project showcases how AI can help businesses make smarter decisions by analyzing relationships between multiple variables.

Why This Matters in Business?
Understanding how multiple factors influence sales is crucial for:

Optimizing Revenue: Identify the right balance between price and advertising spend.
Efficient Budget Allocation: Invest in marketing where it delivers the highest ROI.
Forecasting Demand: Improve supply chain planning with accurate sales predictions.