Project Template: Getting Started with TensorFlow

Tools and Technologies:

• Primary Framework: TensorFlow
• Additional Libraries: None required for the basic example.

Setup and Installation:

1. Install TensorFlow with CUDA using pip:

   pip install tensorflow[and-cuda]

2. Verify the installation by running the following Python commands:

   import tensorflow as tf
   print("TensorFlow version:", tf.__version__)

• For the specific installation process, refer to the Official Install Document.

Basic TensorFlow Operations:

1. Perform a simple addition operation using TensorFlow:

   import tensorflow as tf
   
   # Define constants
   const1 = tf.constant([[1,2,3], [1,2,3]])
   const2 = tf.constant([[3,4,5], [3,4,5]])
   
   # Perform addition
   result = tf.add(const1, const2)
   
   # In TensorFlow 2.x, you can directly obtain the numerical values using the numpy() method
   print(result.numpy())

Building a Simple Machine Learning Model:

1. Load a dataset, build, and train a machine learning model using TensorFlow:

   import tensorflow as tf
   
   # Load the MNIST dataset
   mnist = tf.keras.datasets.mnist
   (x_train, y_train), (x_test, y_test) = mnist.load_data()
   x_train, x_test = x_train / 255.0, x_test / 255.0
   
   # Build a tf.keras.Sequential model
   model = tf.keras.models.Sequential([
     tf.keras.layers.Flatten(input_shape=(28, 28)),
     tf.keras.layers.Dense(128, activation='relu'),
     tf.keras.layers.Dropout(0.2),
     tf.keras.layers.Dense(10)
   ])

Running the Model:

1. Compile and train the model:

   model.compile(optimizer='adam',
                 loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
                 metrics=['accuracy'])
   
   # Train the model
   model.fit(x_train, y_train, epochs=5)
   
   # Evaluate the model
   model.evaluate(x_test,  y_test, verbose=2)

Template Author:

• Name: Jiaying Wang Email: wangj63@rpi.edu

References:

• TensorFlow 2 Quickstart for Beginners: TensorFlow Official Documentation
• TensorFlow Gradient Example: TensorFlow Core
• TensorFlow Placeholders and Filters Example: RipTutorial