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开源软件名称:full-stack-deep-learning/course-gitbook开源软件地址:https://github.com/full-stack-deep-learning/course-gitbook开源编程语言:开源软件介绍:
Full Stack Deep Learning{% hint style="info" %} We are teaching an updated and improved FSDL as an official UC Berkeley course Spring 2021. Sign up to receive updates on our lectures as they're released — and to optionally participate in a synchronous learning community. Sign up for 2021**** {% endhint %} About this courseSince 2012, deep learning has led to remarkable progress across a variety of challenging computing tasks, from image recognition to speech recognition, robotics, and audio synthesis. Deep learning has the potential to enable a new set of previously infeasible technologies like autonomous vehicles, real-time translation, and voice assistants and help reinvent existing software categories. There are many great courses to learn how to train deep neural networks. However, training the model is just one part of shipping a deep learning project. This course teaches full-stack production deep learning:
This course was originally taught as an in-person boot camp in Berkeley from 2018 - 2019. It was also taught as a University of Washington Computer Science PMP course in Spring 2020. The discussion page for the course on Gitter. The course project is on Github. {% hint style="info" %} Please submit a pull request if any information is out of date or if you have good additional info to add! {% endhint %} Who is this forThe course is aimed at people who already know the basics of deep learning and want to understand the rest of the process of creating production deep learning systems. You will get the most out of this course if you have:
We will not review the fundamentals of deep learning (gradient descent, backpropagation, convolutional neural networks, recurrent neural networks, etc), so you should review those materials first if you are rusty. OrganizersGuest LecturesNewsletter{% embed url="https://forms.gle/mDQZxsLZmep8JFgx9" caption="" %} Course Content{% page-ref page="course-content/setting-up-machine-learning-projects/" %} {% page-ref page="course-content/infrastructure-and-tooling/" %} {% page-ref page="course-content/data-management/" %} {% page-ref page="course-content/ml-teams/" %} {% page-ref page="course-content/training-and-debugging/" %} {% page-ref page="course-content/testing-and-deployment/" %} {% page-ref page="course-content/research-areas.md" %} Guest Lectures{% page-ref page="guest-lectures/xavier-amatriain.md" %} {% page-ref page="guest-lectures/chip-huyen-nvidia.md" %} {% page-ref page="guest-lectures/lukas-biewald-weights-and-biases.md" %} {% page-ref page="guest-lectures/jeremy-howard-fast.ai.md" %} {% page-ref page="guest-lectures/richard-socher-salesforce.md" %} {% page-ref page="guest-lectures/raquel-urtasun-uber-atg.md" %} {% page-ref page="guest-lectures/yangqing-jia-alibaba.md" %} {% page-ref page="guest-lectures/andrej-karpathy-tesla.md" %} {% page-ref page="guest-lectures/jai-ranganathan-keeptruckin.md" %} {% page-ref page="guest-lectures/franziska-bell-toyota-research.md" %} |
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