TensorFlow培训

TensorFlow培训

TensorFlow is a 2nd Generation API of Google's open source software library for Deep Learning.

NobleProg onsite live TensorFlow training courses demonstrate through hands-on practice how to use the TensorFlow system to facilitate research in machine learning, and to make it quick and easy to transition from research prototype to production system.

TensorFlow training is available in various formats, including onsite live training and live instructor-led training using an interactive, remote desktop setup. Local TensorFlow training can be carried out live on customer premises or in NobleProg local training centers.

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TensorFlow大纲

代码 名字 时长 概览
tf101 Deep Learning with TensorFlow 21小时 TensorFlow is a 2nd Generation API of Google's open source software library for Deep Learning. The system is designed to facilitate research in machine learning, and to make it quick and easy to transition from research prototype to production system. Audience This course is intended for engineers seeking to use TensorFlow for their Deep Learning projects After completing this course, delegates will: understand TensorFlow’s structure and deployment mechanisms be able to carry out installation / production environment / architecture tasks and configuration be able to assess code quality, perform debugging, monitoring be able to implement advanced production like training models, building graphs and logging
tfir TensorFlow for Image Recognition 28小时 This course explores, with specific examples, the application of Tensor Flow to the purposes of image recognition Audience This course is intended for engineers seeking to utilize TensorFlow for the purposes of Image Recognition After completing this course, delegates will be able to: understand TensorFlow’s structure and deployment mechanisms carry out installation / production environment / architecture tasks and configuration assess code quality, perform debugging, monitoring implement advanced production like training models, building graphs and logging
dlv Deep Learning for Vision 21小时 Audience This course is suitable for Deep Learning researchers and engineers interested in utilizing available tools (mostly open source ) for analyzing computer images This course provide working examples.
Neuralnettf Neural Networks Fundamentals using TensorFlow as Example 28小时 This course will give you knowledge in neural networks and generally in machine learning algorithm,  deep learning (algorithms and applications). This training is more focus on fundamentals, but will help you choosing the right technology : TensorFlow, Caffe, Teano, DeepDrive, Keras, etc. The examples are made in TensorFlow.
datamodeling Pattern Recognition 35小时 This course provides an introduction into the field of pattern recognition and machine learning. It touches on practical applications in statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. The course is interactive and includes plenty of hands-on exercises, instructor feedback, and testing of knowledge and skills acquired. Audience     Data analysts     PhD students, researchers and practitioners  
tpuprogramming TPU Programming: Building Neural Network Applications on Tensor Processing Units 7小时 The Tensor Processing Unit (TPU) is the architecture which Google has used internally for several years, and is just now becoming available for use by the general public. It includes several optimizations specifically for use in neural networks, including streamlined matrix multiplication, and 8-bit integers instead of 16-bit in order to return appropriate levels of precision. In this instructor-led, live training, participants will learn how to take advantage of the innovations in TPU processors to maximize the performance of their own AI applications. By the end of the training, participants will be able to: Train various types of neural networks on large amounts of data Use TPUs to speed up the inference process by up to two orders of magnitude Utilize TPUs to process intensive applications such as image search, cloud vision and photos Audience Developers Researchers Engineers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
embeddingprojector Embedding Projector: Visualizing your Training Data 14小时 Embedding Projector is an open-source web application for visualizing the data used to train machine learning systems. Created by Google, it is part of TensorFlow. This instructor-led, live training introduces the concepts behind Embedding Projector and walks participants through the setup of a demo project. By the end of this training, participants will be able to: Explore how data is being interpreted by machine learning models Navigate through 3D and 2D views of data to understand how a machine learning algorithm interprets it Understand the concepts behind Embeddings and their role in representing mathematical vectors for images, words and numerals. Explore the properties of a specific embedding to understand the behavior of a model Apply Embedding Project to real-world use cases such building a song recommendation system for music lovers Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
tensorflowserving TensorFlow Serving 7小时 TensorFlow Serving is a system for serving machine learning (ML) models to production. In this instructor-led, live training, participants will learn how to configure and use TensorFlow Serving to deploy and manage ML models in a production environment. By the end of this training, participants will be able to: Train, export and serve various TensorFlow models Test and deploy algorithms using a single architecture and set of APIs Extend TensorFlow Serving to serve other types of models beyond TensorFlow models Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
mlbankingpython_ 机器学习用于银行业务(使用Python) 21小时 在这一由讲师引导的现场培训中,参与者将学习如何应用机器学习技术和工具来解决银行业的现实问题。Python将被用作编程语言。 参与者首先学习关键原则,然后通过建立自己的机器学习模型并使用模型来完成一些现场项目以将所学知识运用到实践中。 受众 开发人员 数据科学家 课程形式 部分讲座、部分讨论、练习和大量实操
undnn Understanding Deep Neural Networks 35小时 This course begins with giving you conceptual knowledge in neural networks and generally in machine learning algorithm, deep learning (algorithms and applications). Part-1(40%) of this training is more focus on fundamentals, but will help you choosing the right technology : TensorFlow, Caffe, Theano, DeepDrive, Keras, etc. Part-2(20%) of this training introduces Theano - a python library that makes writing deep learning models easy. Part-3(40%) of the training would be extensively based on Tensorflow - 2nd Generation API of Google's open source software library for Deep Learning. The examples and handson would all be made in TensorFlow. Audience This course is intended for engineers seeking to use TensorFlow for their Deep Learning projects After completing this course, delegates will: have a good understanding on deep neural networks(DNN), CNN and RNN understand TensorFlow’s structure and deployment mechanisms be able to carry out installation / production environment / architecture tasks and configuration be able to assess code quality, perform debugging, monitoring be able to implement advanced production like training models, building graphs and logging   Not all the topics would be covered in a public classroom with 35 hours duration due to the vastness of the subject. The Duration of the complete course will be around 70 hours and not 35 hours.
dlfornlp Deep Learning for NLP (Natural Language Processing) 28小时 Deep Learning for NLP allows a machine to learn simple to complex language processing. Among the tasks currently possible are language translation and caption generation for photos. DL (Deep Learning) is a subset of ML (Machine Learning). Python is a popular programming language that contains libraries for Deep Learning for NLP. In this instructor-led, live training, participants will learn to use Python libraries for NLP (Natural Language Processing) as they create an application that processes a set of pictures and generates captions.  By the end of this training, participants will be able to: Design and code DL for NLP using Python libraries Create Python code that reads a substantially huge collection of pictures and generates keywords Create Python Code that generates captions from the detected keywords Audience Programmers with interest in linguistics Programmers who seek an understanding of NLP (Natural Language Processing)  Format of the course Part lecture, part discussion, exercises and heavy hands-on practice

近期课程

课程日期价格【远程 / 传统课堂】
机器学习用于银行业务(使用Python) - 新东方大厦星期一, 2018-03-12 09:30¥28810 / ¥30010
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本次培训的第一部分(40%)更侧重于基础知识,但将帮助您选择正确的技术:TensorFlow,Caffe,Theano,DeepDrive,Keras等。 完成本课程后,学员将:了解TensorFlow的结构和部署机制,能够执行安装/生产环境/架构任务和配置,以评估代码质量,进行调试,监控,能够实现培训模型,建筑图形和日志等先进的生产读者本课程适合深度学习的研究人员和工程师,他们对利用可用工具(主要是开源软件)进行计算机图像分析感兴趣。 本次培训的第二部分(20%)介绍了Theano - 一个使得深度学习模型写得容易的python库。 观众数据分析博士生,研究人员和从业人员TensorFlow是Google深度学习开源软件库的第二代API。 在这次由讲师主导的现场培训中,与会者将学习如何利用TPU处理器的创新优势,最大限度地提高自己AI应用的性能。