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📐 ML Fundamentals

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

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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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