How To Code A Neural Network From Scratch Part 6 - Convergence

TL;DR

By allowing a simplistic neural network model to run longer, the accuracy can be significantly improved.

Transcript

welcome back everybody Phil here thanks for joining me for our tutorial series on building a neural network from scratch we left off in the last episode we had just finished our neural network model and we discovered that only after 50 epochs or maybe it was a hundred we had an accuracy of around 91% which is pretty good now in the grand scheme of ... Read More

Key Insights

• 😘 The neural network model initially achieves an accuracy of around 91%, which is considered low.
• 👻 Allowing the model to run for a longer period significantly improves its accuracy.
• 🐢 The resource usage of the neural network model is not too demanding, even on a relatively slower CPU.
• 🚠 The simplistic model, with only two hidden layers and 75 units, is able to achieve an accuracy of over 95%.

Questions & Answers

Q: How can the accuracy of a simplistic neural network model be improved?

The accuracy of a simplistic neural network model can be improved by allowing it to run for a longer period, enabling it to learn and train more effectively.

Q: Why is the initial accuracy of the neural network model considered low?

The initial accuracy of the neural network model is considered low because it is a simplistic model with only two hidden layers and 75 units, which limits its capacity to accurately predict outcomes.

Q: What is the purpose of tracking the cost and prediction accuracy between epochs?

Tracking the cost and prediction accuracy between epochs helps visualize how these metrics evolve over time, giving insights into the learning progress and performance of the neural network model.

Q: How can plotting the cost and prediction accuracy help evaluate the neural network model?

Plotting the cost and prediction accuracy allows for visualizing how these metrics change over time, enabling the evaluation of the neural network model's performance and identifying areas of improvement.

Summary & Key Takeaways

• The tutorial series focuses on building a neural network from scratch.

• The accuracy of the neural network model is initially around 91%, which is considered low.

• By allowing the model to run for a longer period, the accuracy can be improved significantly.