/Animation-of-Linear-Regression-Model-with-Tensorflow

Utilizing Tensorflow's animation capabilities to visualize a Linear Regression model built for predicting House Prices.

Primary LanguagePython

Animation of Linear Regression Model with Tensorflow

In this project, we utilize Tensorflow's animation capabilities to visualize a Linear Regression model built for predicting House Prices.

As outlined in Jerry Kurata's wonderful course from Pluralsight, Training a Model with TensorFlow has two prime aspects:

  • Concept
  • Implementation

We achieve the Conceptualization phase by following these steps:

  • Preparation of the Data
  • Inference
  • Loss Measurement
  • Optimizer to Minimize Loss

The corresponding Implementation steps followed are:

  • Generation house size and price data
  • Defining inference as : Price = (sizeFactor * size) + priceOffset
  • Using Mean Square Error for loss measurement
  • using Gradient Descent Optimizer

Python Libraries and functions used include:

  • tensorflow, numpy, math, matplotlib.pyplot, matplotlib.animation, numpy.random, plt.plot, plt.xlabel, plt.ylabel, plt.show
  • matplotlib.animation used for animation of the plot to watch fitting of the line IN ACTION!