Mini Project

Image-classification-with-TensorFlow

Built a neural network model to solve a basic image classification problem, on MNIST dataset.

Dataset: MNIST dataset

Steps Involved:

1. Import Packages (numpy, tensorflow, matplotlib)
2. Load Data (load the data and split the data into train and test)
3. One Hot Encoding (labels)
4. Data Reshaping
5. Data Normalization (Mean and Standard Deviation)
6. Creating a model (structure, layers)
7. Compiling the model (optimizer, loss, metrics)
8. Model fitting
9. Evaluating the model (loss , accuracy)
10. Predictions
11. Plotting (Matplotlib)