Introduction to Handwritten Digits Recognition using TensorFlow: Part 1 😁

Hello and welcome to this tutorial on TensorFlow for beginners! In this tutorial, we will be covering the basics of building a handwritten digits recognition model using TensorFlow. This tutorial is perfect for those who are just getting started with TensorFlow and machine learning.

In this first part of the tutorial, we will focus on setting up our environment and loading the dataset. Let’s get started!

Setting up the environment

First, make sure you have TensorFlow installed on your machine. You can install TensorFlow using pip by running the following command:

pip install tensorflow

Once TensorFlow is installed, you can start writing your code in a Python file. We will be using Python for this tutorial, so make sure you have Python installed on your machine as well.

Loading the dataset

Next, we need to load the handwritten digits dataset that we will be using to train our model. For this tutorial, we will be using the popular MNIST dataset, which consists of 28×28 pixel images of handwritten digits from 0 to 9.

To load the MNIST dataset, we can use the TensorFlow library’s built-in function tf.keras.datasets.mnist.load_data(). This function will download the dataset and return it in the form of training and testing sets.

Here is the code to load the MNIST dataset:

import tensorflow as tf

# Load the MNIST dataset
(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data()

# Normalize and reshape the dataset
x_train, x_test = x_train / 255.0, x_test / 255.0
x_train = x_train.reshape(x_train.shape[0], 28, 28, 1)
x_test = x_test.reshape(x_test.shape[0], 28, 28, 1)

In the above code, we first import the TensorFlow library and then use the tf.keras.datasets.mnist.load_data() function to load the dataset. We then normalize the pixel values of the images by dividing them by 255 and reshape the images to be 28×28 pixels.

Conclusion

That’s it for this first part of the tutorial! In this part, we covered setting up our environment and loading the MNIST dataset. In the next part of the tutorial, we will be building and training our handwritten digits recognition model using TensorFlow. Stay tuned for Part 2!

I hope you found this tutorial helpful and informative. Thank you for reading and happy coding! 😁👍