Exercises | Machine Learning | Google for Developers
Sep 26, 2024 · This page lists the exercises in Machine Learning Crash Course. Programming exercises run directly in your browser (no setup required!) using the Colaboratory platform. …
Machine Learning Crash Course - Google Developers
Google's fast-paced, practical introduction to machine learning, featuring a series of lessons with video lectures, interactive visualizations, and hands-on practice exercises.
Framing an ML problem | Machine Learning - Google Developers
Oct 27, 2023 · After verifying that your problem is best solved using either a predictive ML or a generative AI approach, you're ready to frame your problem in ML terms. You frame a problem in ML terms by completing the following tasks: Define the ideal outcome and the model's goal. Identify the model's output. Define success metrics.
Introduction to Machine Learning Problem Framing
Jul 18, 2022 · Introduction to Machine Learning Problem Framing teaches you how to determine if machine learning (ML) is a good approach for a problem and explains how to outline an ML solution. Estimated Course Length: 45 minutes Objectives:
Machine Learning | Google for Developers
Our guides offer simple step-by-step walkthroughs for solving common machine learning problems using best practices.
Understand the problem | Machine Learning - Google Developers
Oct 9, 2024 · To understand the problem, perform the following tasks: State the goal for the product you are developing or refactoring. Determine whether the goal is best solved using predictive ML, generative AI, or a non-ML solution.
What is clustering? | Machine Learning | Google for Developers
Jul 22, 2024 · Clustering is an unsupervised machine learning technique designed to group unlabeled examples based on their similarity to each other. (If the examples are labeled, this kind of grouping is called classification.) Consider a hypothetical patient study designed to evaluate a new treatment protocol.
What is Machine Learning? | Google for Developers
May 14, 2024 · Machine learning (ML) powers some of the most important technologies we use, from translation apps to autonomous vehicles. This course explains the core concepts behind ML. ML offers a new way to solve problems, answer complex questions, and create new content.
Overview | Machine Learning | Google for Developers
Oct 12, 2023 · Problem framing is the process of analyzing a problem to isolate the individual elements that need to be addressed to solve it. Problem framing helps determine your project's technical feasibility and provides a clear set of goals and success criteria.
Neural networks: Multi-class classification | Machine Learning
Oct 9, 2024 · Learn how neural networks can be used for two types of multi-class classification problems: one vs. all and softmax.