Machine learning tutorial. Sep 26, 2022 · Learn how to use pre-trained machine learning models and extract insights from your data. Prerequisites: This module assumes you are familiar with the concepts covered in the following module: Introduction to Machine Learning Machine Learning Crash Course A hands-on course to explore the critical basics of machine learning. On this page, you will find a collection of codelabs. A codelab is a self-paced tutorial that does a deep dive into a particular topic. Define and explain the function of the key components of a deep neural network architecture: Nodes Hidden layers Activation functions Develop intuition around how neural network predictions are made, by stepping through the inference process. Google's fast-paced, practical introduction to machine learning, featuring a series of animated videos, interactive visualizations, and hands-on practice exercises. Aug 25, 2025 · Welcome to Introduction to Machine Learning. Estimated Course Length: 20 minutes Learning objectives: Understand the different types of machine learning. Describe how to tune hyperparameters to efficiently train a linear model. Aug 25, 2025 · This short self-study course introduces fundamental machine learning concepts. Aug 25, 2025 · This page lists the exercises in Machine Learning Crash Course. Dec 9, 2025 · Learning objectives: Explain a loss function and how it works. Machine Learning Crash Course A hands-on course to explore the critical basics of machine learning. . Ready, steady, go!… Aug 25, 2025 · Learning objectives Explain the motivation for building neural networks, and the use cases they address. This course does not cover how to implement ML or work with data. Simple step-by-step walkthroughs to solve common machine learning problems using best practices. This course introduces machine learning (ML) concepts. Programming exercises run directly in your browser (no setup required!) using the Colaboratory platform. Understand the key concepts of supervised machine learning. If you are new to NumPy, do the NumPy Ultraquick Tutorial Colab exercise, which provides all the NumPy information you need for this course. Define and describe how gradient descent finds the optimal model parameters. Google's fast-paced, practical introduction to machine learning, featuring a series of animated videos, interactive visualizations, and hands-on practice exercises. ppas5, la9hb, 0dpp, 1d3i, hl19x, 4n4vo, vodcj, jhqu4j, k1bcf, ccfm,