Browse Lessons

7.1: Machine Learning as a Web Engineer - putting knowledge into practice

Advanced machine learning for web developers: Autoencoders, GANs, RNNs and more

6.5: Dealing with edge cases in spam detection

6.4.1: Using a natural language model: Comment spam detection - setting up the web scaffolding

6.4.4: Using a natural language model: Comment spam detection - web sockets

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

Level up with Google Developer Student Clubs

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

Google Summer of Code 2023 #Shorts

Google Summer of Code 2023, Cloud Workstations, and more dev news

This is what we mean when we say Google Developer Experts (GDE)

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?

4.2: Gathering, refining, and using data effectively for ML model datasets

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

Interview with Pavlo Stavytskyi, Android contributor to Google Dev Library

2023 Solution Challenge: Global kick-off event

Google for Startups Accelerator: Climate change #Shorts

17 Days of Flutter, optimizing TensorFlow Processors, and more dev news!

Building community with GDG Lawrence

Hash Code Hubs are back for 2023 - Apply to host a Hub!

3.6.2: Using advanced pre-trained Web ML models - Part 2: Use MoveNet for pose estimation in browser

Exploring Tensorflow Hub: Using pre-trained web ML models

Tutorial: How to use raw tensorFlow.js pre-trained models in browser

TensorFlow fundamentals: What are tensors in TensorFlow.js?

Tutorial: Make a web-based smart camera with the COCO-SSD machine learning model in TensorFlow

3.3.5: Make your own web based smart camera in JS - Part 5

3.3.4: Make your own web based smart camera in JS - Part 4

3.3.3: Build a web based smart camera in JavaScript - Part 3

3.3.2: Make your own web based smart camera in JS - Part 2

3.3.1: Make your own web based smart camera in JS - Part 1

3.2: Selecting an ML model to use