Log in
E-mail
Password
Remember
Forgot password ?
Become a member for free
Sign up
Sign up
New member
Sign up for FREE
New customer
Discover our services
Settings
Settings
Dynamic quotes 
OFFON

MarketScreener Homepage  >  Equities  >  Nasdaq  >  Microsoft Corporation    MSFT

MICROSOFT CORPORATION

(MSFT)
  Report
Delayed Quote. Delayed Nasdaq - 11/27 01:00:00 pm
215.23 USD   +0.64%
11/27SALESFORCE, DELTA AIR LINES, BEST BUY : Stocks That Defined the Week
DJ
11/27NEWS HIGHLIGHTS : Top Company News of the Day
DJ
11/27NEWS HIGHLIGHTS : Top Company News of the Day
DJ
SummaryQuotesChartsNewsCalendarCompanyFinancialsConsensusRevisions 
SummaryMost relevantAll NewsPress ReleasesOfficial PublicationsSector newsMarketScreener StrategiesAnalyst Recommendations

Microsoft : makes AI debugging and visualization tool TensorWatch open source

06/27/2019 | 12:00pm EST

[Attachment]

The rise of deep learning is accompanied by ever-increasing model complexity, larger datasets, and longer training times for models. When working on novel concepts, researchers often need to understand why training metrics are trending the way they are. So far, the available tools for machine learning training have focused on a 'what you see is what you log' approach. As logging is relatively expensive, researchers and engineers tend to avoid it and rely on a few signals to guesstimate the cause of the patterns they see. At Microsoft Research, we've been asking important questions surrounding this very challenge: What if we could dramatically reduce the cost of getting more information about the state of the system? What if we had advanced tooling that could help researchers make more informed decisions effectively?

Introducing TensorWatch

We're happy to introduce TensorWatch, an open-source system that implements several of these ideas and concepts. We like to think of TensorWatch as the Swiss Army knife of debugging tools with many advanced capabilities researchers and engineers will find helpful in their work. We presented TensorWatch at the 2019 ACM SIGCHI Symposium on Engineering Interactive Computing Systems.

Custom UIs and visualizations

The first thing you might notice when using TensorWatch is it extensively leverages Jupyter Notebook instead of prepackaged user interfaces, which are often difficult to customize. TensorWatch provides the interactive debugging of real-time training processes using either the composable UI in Jupyter Notebooks or the live shareable dashboards in Jupyter Lab. In addition, since TensorWatch is a Python library, you can also build your own custom UIs or use TensorWatch in the vast Python data science ecosystem. TensorWatch also supports several standard visualization types, including bar charts, histograms, and pie charts, as well as 3D variations.

With TensorWatch-a debugging and visualization tool for machine learning-researchers and engineers can customize the user interface to accommodate a variety of scenarios. Above is an example of TensorWatch running in Jupyter Notebook, rendering a live chart from multiple streams produced by an ML training application.

Streams, streams everywhere

One of the central premises of the TensorWatch architecture is we uniformly treat data and other objects as streams. This includes files, console, sockets, cloud storage, and even visualizations themselves. With a common interface, TensorWatch streams can listen to other streams, which enables the creation of custom data flow graphs. Using these concepts, TensorWatch trivially allows you to implement a variety of advanced scenarios. For example, you can render many streams into the same visualization, or one stream can be rendered in many visualizations simultaneously, or a stream can be persisted in many files, or not persisted at all. The possibilities are endless!

TensorWatch supports a variety of visualization types. Above is an example of a TensorWatch t-SNE visualization of the MNIST dataset.

Lazy logging mode

With TensorWatch, we also introduce lazy logging mode. This mode doesn't require explicit logging of all the information beforehand. Instead, you can have TensorWatch observe the variables. Since observing is basically free, you can track as many variables as you like, including large models or entire batches during the training. TensorWatch then allows you to perform interactive queries that run in the context of these variables and returns the streams as a result. These streams can then be visualized, saved, or processed as needed. For example, you can write a lambda expression that computes mean weight gradients in each layer in the model at the completion of each batch and send the result as a stream of tensors that can be plotted as a bar chart.

Phases of model development

At Microsoft Research, we care deeply about improving debugging capabilities in all phases of model development-pre-training, in-training, and post-training. Consequently, TensorWatch provides many features useful for pre- and post-training phases as well. We lean on several excellent open-source libraries to enable many of these features, which include model graph visualization, data exploration through dimensionality reduction, model statistics, and several prediction explainers for convolution networks.

Open source on GitHub

We hope TensorWatch helps spark further advances and ideas for efficiently debugging and visualizing machine learning and invite the ML community to participate in this journey via GitHub.

Disclaimer

Microsoft Corporation published this content on 27 June 2019 and is solely responsible for the information contained therein. Distributed by Public, unedited and unaltered, on 27 June 2019 15:59:02 UTC


© Publicnow 2019
All news about MICROSOFT CORPORATION
11/27SALESFORCE, DELTA AIR LINES, BEST BU : Stocks That Defined the Week
DJ
11/27NEWS HIGHLIGHTS : Top Company News of the Day
DJ
11/27NEWS HIGHLIGHTS : Top Company News of the Day
DJ
11/27EXCLUSIVE : Suspected North Korean hackers targeted COVID vaccine maker AstraZen..
RE
11/27NEWS HIGHLIGHTS : Top Company News of the Day
DJ
11/27NEWS HIGHLIGHTS : Top Company News of the Day
DJ
11/27NEWS HIGHLIGHTS : Top Company News of the Day
DJ
11/27NEWS HIGHLIGHTS : Top Company News of the Day
DJ
11/27NEWS HIGHLIGHTS : Top Company News of the Day
DJ
11/27NEWS HIGHLIGHTS : Top Company News of the Day
DJ
More news
Financials (USD)
Sales 2021 158 B - -
Net income 2021 51 344 M - -
Net cash 2021 76 102 M - -
P/E ratio 2021 31,9x
Yield 2021 1,01%
Capitalization 1 627 B 1 627 B -
EV / Sales 2021 9,81x
EV / Sales 2022 8,76x
Nbr of Employees 163 000
Free-Float 99,9%
Chart MICROSOFT CORPORATION
Duration : Period :
Microsoft Corporation Technical Analysis Chart | MSFT | US5949181045 | MarketScreener
Technical analysis trends MICROSOFT CORPORATION
Short TermMid-TermLong Term
TrendsNeutralNeutralBullish
Income Statement Evolution
Consensus
Sell
Buy
Mean consensus BUY
Number of Analysts 39
Average target price 242,47 $
Last Close Price 215,23 $
Spread / Highest target 29,2%
Spread / Average Target 12,7%
Spread / Lowest Target -16,4%
EPS Revisions
Managers
NameTitle
Satya Nadella Chief Executive Officer & Non-Independent Director
Bradford L. Smith President & Chief Legal Officer
John Wendell Thompson Independent Chairman
Kirk Koenigsbauer COO & VP-Experiences & Devices Group
Amy E. Hood Chief Financial Officer & Executive Vice President
Sector and Competitors
1st jan.Capitalization (M$)
MICROSOFT CORPORATION35.62%1 627 246
OKTA, INC.104.59%30 234
BEIJING KINGSOFT OFFICE SOFTWARE, INC.89.34%22 066
HUNDSUN TECHNOLOGIES INC.42.84%13 611
NUANCE COMMUNICATIONS, INC.140.44%12 088
PAYLOCITY HOLDING CORPORATION65.84%10 869