Intro To Deep Learning
Leon Noel

RC Ascend
Agenda
-
Questions?
-
Let's Talk - Learning
-
Learn - What is Machine, Deep, Ect Learning?
-
Learn - What is a model?
-
Learn - Bird or Not Model?
-
Do - Read Paper + Watch 1.2
-
Homework - Week 01 Fast.ai
Questions
About last class or life

Resetting Forgetting Curve

https://www.pearsoned.com/three-simple-research-based-ways-to-ace-a-test
Active Recall & Spaced Repetition

Ali Abdaal: https://youtu.be/Z-zNHHpXoMM
Trough Of Sorrow

Manage Frustration
Consistency
Taking Care Of Yourself

AI

A computer will do what you tell it to do.

What is artificial intelligence?
Creation of computer systems that can perform tasks typically requiring human intelligence

Classification
Prediction

DATA
Prediction

What is machine learning?
Creation of computer systems that can perform a task without be explicitly programmed to complete that task that typically requires structured data






https://www.kaggle.com/datasets/alessiocorrado99/animals10
cat
cat
cat
elephant
elephant
elephant
What is deep learning?
Creation of computer systems that can perform a task without be explicitly programmed to complete that task that typically DOES NOT require
structured data






https://www.kaggle.com/datasets/alessiocorrado99/animals10
DATA
Prediction

Training Set
Test Set
DATA
Training
Data

Test
Data
78 %
Algorithm

Algorithm
Linear Regression
Decision Tree

Manual Feature Engineering

Algorithm

Convolutional Neural Networks (CNNs)

Automatic Feature Engineering
Training
Data

Test
Data
78 %
Algorithm
Error Function
accuracy_score(prediction, test_data)
Output = Model
Model by itself is just an empty brain that has not yet learned anything

Weights represent the knowledge that the model has learned from the
training data
The primary function of a model is to make predictions or classifications based on input data. The weights are what allow the model to perform this function accurately. Without weights, the model cannot process the input data correctly to produce meaningful outputs.

Model trained to recognize cars will have weights that enable it to distinguish different cars
Model + Weights = Accurate Predictions
hopefully
Fine-tuning?
adjusting weights to minimize error
Bird or Not

What would be the Machine Learning approach?
What would be the Deep Learning approach?
Training
vs
Inference
Training
Training is the process of teaching the model using historical data, adjusting weights to minimize error
What would training look like for
"Bird or Not"
Inference
Inference is using the trained model to make predictions on new data.
What is used in production?
Homework

Intro To Deep Learning
By Leon Noel
Intro To Deep Learning
- 457