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Google for Developers · Technology

Google for Developers

Subscribe to join a community of creative developers and learn the latest in Google technology — from AI and cloud, to mobile and web. Explore more at developers.google.com

Episodes

6.3: Natural language processing (NLP) - understanding written text

6.4.2: Using a natural language model: Comment spam detection - loading a pretrained NLP model

6.4.3: Using a natural language model: Comment spam detection - word tokenization

6.6: Using a retrained spam detection model in the web browser with TensorFlow.js

6.1: Using models from Python in the web browser with TensorFlow.js

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

Recognize custom objects with TensorFlow.js.

5.3: Using layers models for transfer learning

5.1: Transfer learning: Retraining existing models in the web browser with TensorFlow.js

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

4.7.1: Beyond perceptrons: Convolutional Neural Network (CNNs) in the web browser

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

ML tutorial: How to solve classification problems with TensorFlow and multi-layer perceptrons

4.5.2: Multi-layer perceptrons - Deep neural networks for non linear data

4.5.1: Multi-layer perceptrons - The limits of a single neuron

TensorFlow.js tutorial: A neuron implementation for linear regression

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

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

ML tutorial: How to train neurons

4.3.1: What's a neuron?

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