在Google Cloud上使用TensorFlow进行机器学习

使用TensorFlow构建、训练和部署ML模型:谷歌云强大基础设施的实践之旅，如果你是一名初露头角的数据爱好者、开发人员，甚至是一名经验丰富的专业人士，想要进入不断发展的机器学习世界，你是否经常想知道如何将TensorFlow的强大功能与Google Cloud的巨大可扩展性集成起来？你梦想无缝地部署健壮的ML模型而没有基础设施管理的麻烦吗？
通过我们的结构化指南“在Google Cloud上使用TensorFlow进行机器学习”，深入研究机器学习领域这门课不仅仅是理论。这是一次实践之旅，专门为帮助您在Google Cloud提供的庞大基础设施上利用TensorFlow的实力而量身定制。Machine Learning with TensorFlow on Google Cloud

课程时长:5小时 13分钟 |视频:. MP4，1280×720 30 fps |语言：英语+中英文字幕（云桥网络 机译）含课程文件


你会学到什么
掌握简单ML模型背后的基本原理，例如使用TensorFlow的线性和逻辑回归模型。
构建复杂的人工神经网络(ANN)来应对更复杂的数据挑战。
为图像和模式识别任务设计卷积神经网络(CNN)。
利用Google Cloud的Colab的能力，高效地为ML任务执行Python代码。
探索Google Vertex的功能以及它如何增强Jupyter笔记本的构造。
实施端到端的机器学习工作流，从数据预处理到模型部署

要求
Python基础知识，熟悉Jupyter笔记本；初学者欢迎，因为基础概念涵盖。

在本课程中，您将
发展
使用TensorFlow的线性和逻辑回归等基础模型。
掌握
高级架构，如用于复杂任务的人工神经网络(ANN)和卷积神经网络(CNN)。
马具
Google Cloud的Colab轻松运行Python代码的能力和便利。
建造
复杂的Jupyter笔记本，带有Google Colab和Vertex上的真实世界数据集。
但是为什么要在Google Cloud上一头扎进TensorFlow呢？随着机器学习解决方案在决策、预测趋势和理解海量数据集方面变得越来越重要，TensorFlow与谷歌云的集成是快速原型开发、可扩展计算和经济高效的解决方案的关键。
在整个学习旅程中，您将沉浸在一系列项目和练习中，从构建您的第一个ML模型到在云上部署复杂的深度学习网络。
本课程与众不同，因为它弥合了理论和实际部署之间的差距，确保一旦完成本课程，您不仅知识渊博，而且真正准备好在现实世界中应用这些技能。
在你的机器学习冒险中迈出下一步。加入我们，让我们一起构建、部署和扩展。

这门课程是给谁的
热衷于使用TensorFlow探索机器学习的有志数据爱好者。
寻求利用云基础设施完成ML任务的开发人员。
渴望将TensorFlow的功能与谷歌云相结合的专业人士。
寻求关于云上ML的结构化介绍的初学者。
有经验的学习者旨在通过使用GCP上的TensorFlow加深他们在ML领域的知识和技能。

Build, train, and deploy ML models with TensorFlow: A hands-on journey through Google Cloud’s powerful infrastructure

What you’ll learn
Master the foundational principles behind simple ML models such as Linear and Logistic Regression models using TensorFlow.
Construct intricate Artificial Neural Networks (ANN) to tackle more complex data challenges.
Design Convolutional Neural Networks (CNN) for image and pattern recognition tasks.
Harness the capabilities of Google Cloud’s Colab to execute Python codes for ML tasks efficiently.
Explore the functionalities of Google Vertex and how it augments Jupyter notebook constructions.
Implement end-to-end machine learning workflows, from data preprocessing to model deployment

Requirements
Basic knowledge of Python and familiarity with Jupyter notebooks; beginners welcome, as foundational concepts are covered.
Description
If you’re a budding data enthusiast, developer, or even an experienced professional wanting to make the leap into the ever-growing world of machine learning, have you often wondered how to integrate the power of TensorFlow with the vast scalability of Google Cloud? Do you dream of deploying robust ML models seamlessly without the fuss of infrastructure management?
Delve deep into the realms of machine learning with our structured guide on “Machine Learning with TensorFlow on Google Cloud.” This course isn’t just about theory; it’s a hands-on journey, uniquely tailored to help you utilize TensorFlow’s prowess on the expansive infrastructure that Google Cloud offers.
In this course, you will
Develop
foundational models such as Linear and Logistic Regression using TensorFlow.
Master
advanced architectures like Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN) for intricate tasks.
Harness
the power and convenience of Google Cloud’s Colab to run Python code effortlessly.
Construct
sophisticated Jupyter notebooks with real-world datasets on Google Colab and Vertex.
But why dive into TensorFlow on Google Cloud? As machine learning solutions become increasingly critical in decision-making, predicting trends, and understanding vast datasets, TensorFlow’s integration with Google Cloud is the key to rapid prototyping, scalable computations, and cost-effective solutions.
Throughout your learning journey, you’ll immerse yourself in a series of projects and exercises, from constructing your very first ML model to deploying intricate deep learning networks on the cloud.
This course stands apart because it bridges the gap between theory and practical deployment, ensuring that once you’ve completed it, you’re not just knowledgeable but are genuinely ready to apply these skills in real-world scenarios.
Take the next step in your machine learning adventure. Join us, and let’s build, deploy, and scale together.
Who this course is for
Aspiring data enthusiasts keen on exploring machine learning using TensorFlow.
Developers looking to leverage cloud infrastructure for ML tasks.
Professionals eager to combine TensorFlow’s capabilities with Google Cloud.
Beginners seeking a structured introduction to ML on the cloud.
Experienced learners aiming to deepen their knowledge and skillset in the field of ML using TensorFlow on GCP.