Code-Alongs: Neural Networks

Overview

Code-Alongs are live experiences taught by our expert instructors designed to prepare you for concepts found in the sprint challenges. Code-Alongs are your opportunity to work on complex job-ready problems in a live and engaging environment.

Code-Alongs are live classes 50 minutes in length designed to offer deeper insights into learning your core competencies and are offered seven days a week in the morning, afternoon, and evening.

Because Code-Alongs delve deeper into a core competency, you will need to come to class prepared to have the best experience.

Preparation Guidelines

Ideal Code-Along Preparation Checklist:

  • Did you review the core competencies before coming to class?
  • Did you watch the guided projects before coming to class?
  • Did you take the checks for understanding before coming to class?
  • Did you finish your module projects before coming to class?

Code-Along Sessions

Code-Along 1: Architect and Train Neural Networks

In this code-along, you will learn how to architect and train neural networks effectively using Keras.

Related Topics

  • Foundational components of neural networks
  • Perceptrons and activation functions
  • Keras Sequential API implementation
  • Backpropagation and gradient descent
  • Optimizing batch size and learning rate
Starter Notebook Solution Notebook

Code-Along 2: Tune and Regularize Neural Networks

In this code-along, you will learn techniques for tuning hyperparameters and implementing regularization strategies to improve neural network performance.

Related Topics

  • Regularization techniques (L1, L2, dropout)
  • Hyperparameter optimization strategies
  • Weight initialization methods
  • Advanced optimizers (Adam, RMSProp)
  • Early stopping and learning rate schedules
  • Model evaluation and metrics
Starter Notebook Solution Notebook

Additional Resources

For Code-Along 1: Architect and Train Neural Networks

Keras: The Sequential Model Guide TensorFlow: Basic Classification Tutorial 3Blue1Brown: But what is a Neural Network? TensorFlow: Keras Loss Functions Documentation

For Code-Along 2: Tune and Regularize Neural Networks

Keras Tuner Documentation TensorFlow: Hyperparameter Tuning with Keras Tuner Dropout Regularization in Keras Grid Search Hyperparameters for Deep Learning Models