Applied AI with DeepLearning

开始时间: 08/01/2020 持续时间: Unknown

所在平台: Coursera

课程类别: 其他类别

大学或机构: CourseraNew

   

课程主页: https://www.coursera.org/learn/ai

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>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<< This course, Applied Artificial Intelligence with DeepLearning, is part of the IBM Advanced Data Science Certificate which IBM is currently creating and gives you easy access to the invaluable insights into Deep Learning models used by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other disciplines. We’ll learn about the fundamentals of Linear Algebra and Neural Networks. Then we introduce the most popular DeepLearning Frameworks like Keras, TensorFlow, PyTorch, DeepLearning4J and Apache SystemML. Keras and TensorFlow are making up the greatest portion of this course. We learn about Anomaly Detection, Time Series Forecasting, Image Recognition and Natural Language Processing by building up models using Keras on real-life examples from IoT (Internet of Things), Financial Marked Data, Literature or Image Databases. Finally, we learn how to scale those artificial brains using Kubernetes, Apache Spark and GPUs. IMPORTANT: THIS COURSE ALONE IS NOT SUFFICIENT TO OBTAIN THE "IBM Watson IoT Certified Data Scientist certificate". You need to take three other courses where two of them are currently built. The Specialization will be ready late spring, early summer 2018 Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your life. If you’re already an expert, this peep under the mental hood will give your ideas for turbocharging successful creation and deployment of DeepLearning models. If you’re struggling, you’ll see a structured treasure trove of practical techniques that walk you through what you need to do to get on track. If you’ve ever wanted to become better at anything, this course will help serve as your guide. Prerequisites: Some coding skills are necessary. Preferably python, but any other programming language will do fine. Also some basic understanding of math (linear algebra) is a plus, but we will cover that part in the first week as well. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging.

结合使用DeepLearning的AI:&gt;&gt;&gt;通过注册此课程,您同意FAQ中列出的最终用户许可协议。注册后,您可以在“资源”区域中&lt;&lt;&lt; 本课程“带深度学习的应用人工智能”是IBM当前正在创建的IBM高级数据科学证书的一部分,使您可以轻松访问由自然语言处理,计算机视觉,时间序列分析专家使用的对深度学习模型的宝贵见解。 ,以及许多其他学科。我们将学习线性代数和神经网络的基础知识。然后我们介绍最受欢迎的DeepLearning框架,例如Keras,TensorFlow,PyTorch,DeepLearning4J和Apache SystemML。 Keras和TensorFlow构成了本课程的最大部分。我们通过在物联网(IoT),财务标记数据,文献或图像数据库的真实示例中使用Keras构建模型来了解异常检测,时间序列预测,图像识别和自然语言处理。最后,我们学习如何使用Kubernetes,Apache Spark和GPU扩展那些人造大脑。 重要信息:仅凭此课程无法获得“ IBM Watson IoT认证的数据科学家证书”。您还需要参加另外三门课程,其中当前有两门课程在建。该专业将于2018年春季末夏初准备就绪 使用这些方法,无论您想掌握什么主题的技能水平,都可以改变想法并改变生活。如果您已经是专家,那么在脑海中窥探一下您的想法,即可为涡轮增压成功创建和部署DeepLearning模型提供想法。如果您在挣扎中,则会看到一些实用技术的结构化宝库,它们将引导您逐步完成所需的工作。如果您想在任何方面都变得更好,那么本课程将有助于您的指导。 先决条件:一些编码技能是必需的。最好是python,但其他任何编程语言都可以。另外,对数学(线性代数)有一些基本的了解是加分的,但是我们也将在第一周介绍这一部分。 如果您选择参加本课程并获得Coursera课程证书,那么您还将获得IBM数字徽章。要查找有关IBM数字徽章的更多信息,请访问ibm.biz/badging链接。

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This course is part of the IBM Watson IoT Certified Data Scientist certificate which IBM is currentl

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