📐 ML Fundamentals

Neural networks, backpropagation, gradient descent — the maths behind AI

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Testing tip for devs: Test behaviors, not methods.

ML Fundamentals

Testing tip for devs: Test behaviors, not methods.

Google for Developers Intermediate 6d ago

Turing winner David Patterson: how to give AI a bad carbon footprint

ML Fundamentals

Turing winner David Patterson: how to give AI a bad carbon footprint

Google for Developers Intermediate 10mo ago

What's new in the Gemmaverse

ML Fundamentals

What's new in the Gemmaverse

Google for Developers Intermediate 10mo ago

Supercharge your web app with Machine Learning and MediaPipe

ML Fundamentals

Supercharge your web app with Machine Learning and MediaPipe

Google for Developers Intermediate 2y ago

Audio classification - ML on Android with MediaPipe Series

ML Fundamentals

Audio classification - ML on Android with MediaPipe Series

Google for Developers Intermediate 2y ago

6.5: Dealing with edge cases in spam detection

ML Fundamentals

6.5: Dealing with edge cases in spam detection

Google for Developers Intermediate 3y ago

6.2: Converting Python saved models with the TensorFlow.js command line converter

ML Fundamentals

6.2: Converting Python saved models with the TensorFlow.js command line converter

Google for Developers Intermediate 3y ago

4.7.2: Beyond perceptrons: Convolutional Neural Network (CNNs) - Implementation with TensorFlow.js

ML Fundamentals

4.7.2: Beyond perceptrons: Convolutional Neural Network (CNNs) - Implementation with TensorFlow.js

Google for Developers Intermediate 3y ago

4.6.2: Multi-layer perceptrons for classification - Implementing a classifier in TensorFlow.js

ML Fundamentals

4.6.2: Multi-layer perceptrons for classification - Implementing a classifier in TensorFlow.js

Google for Developers Intermediate 3y ago

4.4.2: Implement a neuron for linear regression - Importing and normalizing training data

ML Fundamentals

4.4.2: Implement a neuron for linear regression - Importing and normalizing training data

Google for Developers Intermediate 3y ago

4.4.1: Implement a neuron for linear regression - Training data and outliers

ML Fundamentals

4.4.1: Implement a neuron for linear regression - Training data and outliers

Google for Developers Intermediate 3y ago

4.1: Rolling your own Web ML models from a blank canvas

ML Fundamentals

4.1: Rolling your own Web ML models from a blank canvas

Google for Developers Intermediate 3y ago

3.2: Selecting an ML model to use

ML Fundamentals

3.2: Selecting an ML model to use

Google for Developers Intermediate 3y ago

Building drones to restore deforestation

ML Fundamentals

Building drones to restore deforestation

Google for Developers Intermediate 3y ago

Climbing up the slope of enlightenment in AI and ML

ML Fundamentals

Climbing up the slope of enlightenment in AI and ML

Google for Developers Intermediate 3y ago

Solution Challenge Demo Day 2020 Project: FreeSpeak

ML Fundamentals

Solution Challenge Demo Day 2020 Project: FreeSpeak

Google for Developers Intermediate 5y ago

Real-world image classification using convolutional neural networks | Machine Learning Foundations

ML Fundamentals

Real-world image classification using convolutional neural networks | Machine Learning Foundations

Google for Developers Intermediate 5y ago

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