google crash machine learning machine

Machine Learning Crash Course - Google Developers Blog

2018年3月2日 MLCC covers many machine learning fundamentals, starting with loss and gradient descent, then building through classification models and neural nets. The

Machine Learning Google for Developers

机器学习模型. 这些模块涵盖了构建回归和分类模型的基础知识模型。线性回归简介，涵盖线性模型、损失、梯度下降法和超参数调节。逻辑回归简介，该模型旨在预测给定结果的概率。分

Google Colab

Colab is used extensively in the machine learning community with applications including: Getting started with TensorFlow; Developing and training neural networks; Experimenting with TPUs;...

Exercises Machine Learning Google for Developers

2024年9月26日 This page lists the exercises in Machine Learning Crash Course. Programming exercises run directly in your browser (no setup required!) using the Colaboratory

Neural networks Machine Learning Google for Developers

2024年10月9日 Neural networks. Explain the motivation for building neural networks, and the use cases they address. Develop intuition around how neural network predictions are made,

Machine Learning Google for Developers

Become a better machine learning engineer by following these machine learning best practices used at Google.

大型语言模型 Machine Learning Google for Developers

大型语言模型 Machine Learning Google for Developers. 预计单元时长：45 . 学习目标. 定义几种不同类型的语言模型及其组件。说明如何创建大型语言模型以及上下文和参数。确定

逻辑回归 Machine Learning Google for Developers

机器学习简介. 线性回归. 在线性回归模块中，您探索了如何构建模型来生成连续数值，例如汽车燃料效率。但如果您想构建一个模型来回答“今天会下雨吗？ ”这样的问题，或“这是垃圾邮件

Machine Learning AI Courses Google Cloud Training

Gain real-world machine learning experience using Google Cloud technologies. Learn how to design, build, productionize, optimize, and maintain machine learning systems with this hands-on...

Prerequisites and prework Machine Learning - Google Developers

2024年10月9日 Please read through the following Prework and Prerequisites sections before beginning Machine Learning Crash Course, to ensure you are prepared to complete all the modules.. Prework. Before beginning Machine Learning Crash Course, do the following: If you're new to machine learning, take Introduction to Machine Learning.This short self-study

Categorical data: Vocabulary and one-hot encoding Machine Learning ...

2024年10月9日 Learn how to encode categorical data in feature vectors using one-hot encoding, as well as other techniques to consider for handling outliers and working with high-dimensional categorical features.

Neural networks Machine Learning Google for Developers

2024年10月9日 This course module teaches the basics of neural networks: the key components of neural network architectures (nodes, hidden layers, activation functions), how neural network inference is performed, how neural networks are trained using backpropagation, and how neural networks can be used for multi-class classification problems.

Machine Learning Google for Developers

Discover courses about machine learning fundamentals and core concepts. ... Machine Learning Crash Course A hands-on course to explore the critical basics of machine learning. ... Google Developer Student Clubs Developer consoles. Google API ...

Machine Learning AI Courses Google Cloud Training

Machine learning and artificial intelligence. Did you know that the adoption of machine learning results in 2x more data-driven decisions, 5x faster decision-making, and 3x faster execution? 1 Learn how to implement the latest machine learning and artificial intelligence technology with courses on Vertex AI, BigQuery, TensorFlow, and more.

Overfitting: Model complexity Machine Learning - Google

2024年10月9日 Regularization. Machine learning models must simultaneously meet two conflicting goals: Fit data well. Fit data as simply as possible. One approach to keeping a model simple is to penalize complex models; that is, to force

Fairness: Types of bias Machine Learning - Google Developers

2024年10月9日 Note: The following inventory of biases provides just a small selection of biases that are often uncovered in machine learning datasets; this list is not intended to be exhaustive. Wikipedia's catalog of cognitive biases enumerates over 100 different types of human bias that can affect our judgment.

Fairness: Identifying bias Machine Learning - Google Developers

2024年10月9日 Learn techniques for identifying sources of bias in machine learning data, such as missing or unexpected feature values and data skew.

Logistic Regression Machine Learning Google for Developers

2024年10月9日 Introduction to Machine Learning Linear regression In the Linear regression module , you explored how to construct a model to make continuous numerical predictions, such as the fuel efficiency of a car.

Datasets: Dividing the original dataset Machine Learning Google

2024年10月9日 Traditionally in machine learning, you get those different examples by splitting the original dataset. You might assume, therefore, that you should split the original dataset into two subsets: A training set that the model trains on.

Thresholds and the confusion matrix Machine Learning Google

2024年10月9日 Learn how a classification threshold can be set to convert a logistic regression model into a binary classification model, and how to use a confusion matrix to assess the four types of predictions: true positive (TP), true negative (TN), false positive (FP), and

前提条件和准备工作 Machine Learning Google for Developers

请仔细阅读以下准备工作和开始机器学习之前的前提条件部分速成课程，确保您做好完成所有单元的准备。. 准备工作. 在开始学习机器学习速成课程之前，请执行以下操作：如果您刚开始接触机器学习，请机器简介正在学习。这个简短的自学课程介绍了基本的机器学习概念。

Machine Learning Google for Developers

Become a better machine learning engineer by following these machine learning best practices used at Google. People + AI Guidebook This guide assists UXers, PMs, and developers in collaboratively working through AI design topics and

Learn with Google AI: Making ML education available to everyone

2018年2月28日 From deep learning experts looking for advanced tutorials and materials on TensorFlow, to “curious cats” who want to take their first steps with AI, anyone looking for educational content from ML experts at Google can find it here. Learn with Google AI also features a new, free course called Machine Learning Crash Course (MLCC).

Neural networks: Nodes and hidden layers Machine Learning Google

2024年10月9日 Exercise 1. In the model above, the weight and bias values have been randomly initialized. Perform the following tasks to familiarize yourself with the interface and explore the linear model. You can ignore the Activation Function dropdown for now; we'll discuss this topic later on in the module.. Click the Play ( ️) button above the network to calculate the value of

Machine learning education - TensorFlow

The Machine Learning Crash Course with TensorFlow APIs is a self-study guide for aspiring machine learning practitioners. ... Fundamentals of Google AI for Web Based Machine Learning ... A 3-part series that explores both training and executing machine learned models with TensorFlow.js, ...

Embeddings Machine Learning Google for Developers

2024年10月9日 You want to develop a machine learning (ML) model that can predict food similarity, so your app can make high quality recommendations ("Since you like pancakes, we recommend crepes"). To train your model, you curate a dataset of 5,000 popular meal items, including borscht , hot dog , salad , pizza , and shawarma .

Categorical data: Vocabulary and one-hot encoding Machine Learning ...

Fairness: Test your knowledge Machine Learning - Google

2024年10月9日 Test your knowledge of machine learning fairness concepts by completing this five-question quiz. Machine Learning ... Crash Course Foundational courses Advanced courses Guides Glossary More Quick ... see the Google Developers Site Policies.

Exercises Machine Learning Google for Developers

2024年9月26日 Automated machine learning (30 min) Introduction (10 min) Benefits and limitations (10 min) ... This page lists the exercises in Machine Learning Crash Course. ... For details, see the Google Developers Site Policies.

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