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css-paint-polyfill

CSS Custom Paint / Paint Worklet polyfill with special browser optimizations.

css-triggers

A reference for the render impact of mutating CSS properties.

css_sql_networking_tools

Tools used by the SQL Networking Customer Support Team

cssxpath

Translate CSS selectors to XPath queries.

csu-azurelabs

Hands on labs

cswinrt

C# language projection for the Windows Runtime

ct-policy

cta

Code translation assistance, a feature of Porting Assistant for .NET, helps users automate some aspects of their porting experience using a set of predefined rules and actions.

ctct-provisioning-tool

A tool for provisioning Google Accounts & Analytics leveraging Google's Provisioning API (invite only).

cups

OpenPrinting CUPS Sources

current-versions

Up-to-date listing of Google Chrome's latest versions across stable, beta, dev and canary

custom-tabs-client

Chrome custom tabs examples

cute-pets-example-android-app

cute-pets-example-ios-app

dais

Google Glass presentation aid & analytics tool

daq-server

Server for remote access to National Instruments DAQ devices

dark-mode-toggle

A custom element that allows you to easily put a Dark Mode 🌒 toggle or switch on your site:

dashqy

Tool for querying and displaying Google Analytics and DoubleClick OLAP data

data

Machine-readable data describing Arm architecture and implementations. Includes JSON descriptions of implemented PMU events.

data-accelerator

Data Accelerator for Apache Spark simplifies onboarding to Streaming of Big Data. It offers a rich, easy to use experience to help with creation, editing and management of Spark jobs on Azure HDInsights or Databricks while enabling the full power of the Spark engine.

data-analysis

The aim of this project was to analyse given data set and find out if there exists any trends. The data is produced by a tool similar to Google analytics and the dataset is about a website which is an online repository for books.

data-discovery-using-glue-comprehend

data-intensive-computing

Data-intensive computing deals with storage models, application architectures, middleware, and programming models and tools for large-scale data analytics. In particular we study approaches that address challenges in managing and utilizing ultra-scale data and the methods for transforming voluminous datasets (big data) into discoveries and intelligence for human understanding and decision making. Topics include: intelligent representation of data, approaches discovering intelligence in data, data-driven computing, storage requirements of big data, organization of big data repositories such as Google File System (GFS), characteristics of Write-Once-Read-Many (WORM) data, data-intensive programming models such as MapReduce, fault-tolerance, privacy, security and performance, services-based cloud computing middleware, and scalable analytics and visualization. This course has four major goals: (i) understand data- intensive computing, that has been defined as the fourth paradigm for Science, (ii) study, design and develop solutions using data-intensive computing models such as MapReduce, (iii) predictive analytics and visualization using packages such as R and Google analytics and (iv) focus on methods for scalability using the cloud computing infrastructures such as Google App Engine (GAE), and Amazon Elastic Compute Cloud (EC2).

data-migration-tool

Magento Data Migration Tool

data_science_with_r

Introduction to R R is a programming language, which is an object oriented language created by Statisticians, R provides objects, operators and functions that allow the user to explore, model and visualize data. R is a Programming language Developed at AT&T Bell Lab. It is an open source free language, allowing anyone to use and modify it. R is licensed under the GNU General Public License, with copyright held by The R Foundation For Statistical Computing. It has no need to pay any subscription charges R has a huge active community member. If you have any question about any function any library you can Google it and you would get a proper answer and right the way. As it is an open source language, you, me and lots of Data Scientist, they actually built in all those, inbuilt function and they upload it in a website called CRAN and then you can download all those packages. Over 7800 packages listed on CRAN, here we listed some of the most powerful and commonly used in R packages. R is a cross platform. R can run in different kind of operating system and different hardware. Generally, it is used on GNU/Linux, Macintosh, and Microsoft Windows and running on both 32 and 64-bit processor. R is mainly used for Statistical Analysis and Analytics Purpose, you might be thinking why to learn again another language if you already know many programming languages like JAVA or other programming languages, and think why do you need the language because R is mainly used for all those statistical Analysis and that’s why you should learn the language R. you would understand after doing this course it is actually easy to interpret. R is the leading tool for statistics and data analysis, machine learning as well as. The programming language is more than a statistical package, you can build your own objects, functions, and packages. It is easy to use, the coding style is quite easy. R enables you to interact with many data sources: ODBC -compliant databases (Excel, Access). R also can handle CSV files, SAS, and SPSS, XML and lots of other different files as well. Similarly, it can create a very good visualization. It can produce graphics output in PDF, JPG, PNG and SVG formats and table output for LATEX and HTML. It has a lot of inbuilt functions(packages & Libraries) and the results are also easy to interpret and that’s why lots of industries are using R, it is not about the big or small. Lots of companies like Microsoft, Google are using R actively. It has a big reason, it is free and you can do POC out there. So, be confident about the fact that you are going to learn R and it has huge popularity and your market value is always higher if you know R in Data Science

datadrivenmodel

Build sim from data for use in reinforcement learning and bonsai platform for machine teaching.

datamining_googlemarketingchallenge

Coming up with a prediction algorithm to promote a Vegan Restuarant over Google Ads with the use of Data Mining and Google Analytics tool.

davidstevens

Director of IT & Digital Strategy developing innovative web services solutions for higher education, nonprofits, and small to medium sized businesses. Designing and developing immersive WordPress web experiences featuring API integrations with eCommerce, registration systems, and CRM platforms. Planning and managing digital and content marketing strategies, and measuring user engagement, conversions, and KPIs using Google analytics and data reporting tools.

dbt-ga-bq-replicate

Data build tool model for replicating 3 Google Analytics reports using BigQuery GA export data.

dcv-color-primitives

DCV Color Primitives Library