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Invest Your Time in the Right Skills to Become a Data Scientist in 2021

March 4, 2021 TIBCO Spotfire

Reading Time: 2 minutes

When it comes to new year’s resolutions that involve career moves or goals, it may take months or even years to accomplish such aims. For example, to become a data scientist, you must put in the work, gain experience with your own passion projects, and develop your skills over time to really change your career path.

It can be hard to know where to start and often investing time in the wrong skills can distract you from reaching your end goal. In a recent webinar, Steven Hillion and Catalina Herrera answered questions from the data science community on where to focus your energy and how to get hired as a data scientist in 2021.

How to get started and gain experience?

Oftentimes when you’re coming right out of university, you may feel you have little or no working experience. It’s the classic chicken and the egg problem. I need a job to gain experience, but I don’t have the experience to get the job. In this case, Hillion advises, “Don’t rely on just the classes you’ve taken and the projects you’ve done as a part of those classes.”

Even if you’re unable to get an internship, self-motivated projects using public data are a great way to get your foot in the door and show a natural curiosity by exploring data and answering your own questions. Also, non-profits and small businesses could use volunteers to solve their problems with their data. Herrera cautions however to “ensure whatever you put your energy in that you are passionate about it, have some background in it, and understand the topic.” This helps make the process both fun and fulfilling.

What kinds of hands-on experience do you need?

Ground level, you need some type of statistical and machine learning experience. It’s a very broad field, but there are core techniques and methods that you should be familiar with, including classification, regression, clustering, dimensionality reduction, text analytics, time series, as well as basic statistical and probability functions.

There’s really no shortage of free resources to learn about methods and how to apply your data science knowledge. In fact, at TIBCO we have Doctor Data Science and Doctor Spotfire, which are monthly programs where TIBCO data scientists will take you through a couple of standard techniques. Past sessions are available on Youtube, covering everything from neural networks to time series to categorical encoding.

What technical skills need to be part of your resume?

Python is the obvious thing to mention. R is still current, but Python is the place to start. Although, the most commonly used programming language remains SQL. Nothing new there, but is the language of data and very important to know. It’s fairly straightforward and scalable. For big data, Spark is worth learning as well. And beyond languages, you’ll want at least a college-level class in statistics and online classes on machine learning.

How to find a job?

May feel like you’re throwing your resume into a black hole if you’re just applying to job boards. Leverage your network and find a way to connect to the jobs that appeal to you through your network or through projects that the team may be working on currently. Recruiting fairs and meetups are also helpful in making connections.

The process of becoming a data scientist and getting hired can feel overwhelming but remember you’re not alone and we want to help. Make sure to watch the full webinar for more expert advice and insight into the hiring process.

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The TIBCO Blog

TIBCO4Good and She Loves Data Offer Free Data Skills Workshops During a Time of Vulnerability

January 20, 2021 TIBCO Spotfire

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New to designing meaningful, interactive data visualizations and dashboards? Want to learn how to better understand and prepare your data? Then TIBCO4Good^™’s recently launched “Back on Your Feet” program is for you. Built in partnership with Singapore Management University (SMU) and She Loves Data, this global program can help you up your data visualization and dashboard building skills and stay competitive in today’s professional job market.

Back on Your Feet Program: Empowering Individuals Impacted by the Pandemic

The “Back on Your Feet” program was designed specifically to help educate individuals affected by the global COVID-19 pandemic. It offers a series of workshops and training sessions to empower individuals who may have lost their jobs due to the pandemic and want to increase their competitiveness in an increasingly tough marketplace.

SMU, a premier university in Asia, internationally recognized for its research and distinguished teaching, has developed the course content, including discussions on how to design, develop, and deploy analytic dashboards. “The pandemic has upended the lives and livelihoods of many around the world. As an engaged city university with a strong suite of expertise in computing research and education, the School of Computing and Information Systems is keen to contribute to this meaningful program by TIBCO through our partnership with She Loves Data to upskill and re-skill individuals impacted by the economic malaise, thereby creating a positive impact on the community in Singapore and beyond,” said Professor Pang Hwee Hwa, Dean of SMU School of Computing and Information Systems.

TIBCO4Good and She Loves Data Offer Free Data Skills Workshops During a Time of Vulnerability — From left to right: Nina Conseil, Global Certification Programs at She Loves Data, Bernard Tay and Justin Choy are Teaching Assistants and Rafael J. Barros is Senior Lecturer at the School of Computing and Information Systems, Singapore Management University

Program Benefits and Session Structure

Upon completion of the workshops, participants are certified as dashboard and forecasting specialists and receive a free TIBCO Spotfire^® license for a year. The program began in APJ in November and December 2020, will extend to the U.S. in early 2021, followed closely by EMEA.

Here’s a quick overview of the program structure:

Module 1: Dashboard exploration as an end user; Marking and filtering concepts
Module 2: Asking the right questions by understanding what data is important; Foundations of charts and basic visualizations
Module 3: Basics in data cleaning, advanced visualizations, and connecting to multiple data sources
Module 4: Designing the dashboard for end-user consumption

Your Chance to Up Your Dashboarding Skills

Join us for the second edition of a series of four training modules designed to help you become a dashboard specialist. In the first session, 230 attendees participated actively in the program. Register now for the next event on February 20th!
And to learn more about other TIBCO4Good initiatives helping communities around the world, head to www.tibco.com/tibco4good.

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The TIBCO Blog

Amazon releases long-form speaking style for Alexa skills

April 16, 2020 Big Data

Amazon today announced a long-form Alexa speaking style for news and music content within third-party skills (i.e., voice apps). Starting this week in the U.S., Alexa voice app developers will be able to use a long-form voice that’s optimized for large amounts of information, like articles and podcasts. For example, they could use it to read web pages or a storytelling portion of a game.

The new speaking style could improve experiences by making read-aloud text sound more natural, and by extension boost overall user engagement. Additionally, it could save developers cash and effort by eliminating the need to hire professional voice actors, as well as hours spent recording audio in a studio.

Amazon says the long-from speaking style is powered by a machine learning text-to-speech model that incorporates natural pauses while transitioning from one paragraph to the next, or even from one dialog to another between different characters. That’s akin to a recently launched Google Assistant feature that reads longform content on websites and Android app content, using a more natural and humanlike voice.

Beyond the long-form speaking style, Amazon says that developers can now use the news and conservational speaking styles from Amazon Polly, Amazon’s cloud service that converts text into lifelike speech, for select voices — Matthew, Joanna, and Lupe — in Alexa skills. The news speaking style sound similar to what you might hear from TV news anchors and radio hosts, while the conversational speaking style makes the voices sound less formal and as if they’re speaking to friends and family.

Amazon detailed its work on AI-generated speech in a research paper late last year (“Effect of data reduction on sequence-to-sequence neural TTS”), in which researchers described a system that can learn to adopt a new speaking style from just a few hours of training — as opposed to the tens of hours it might take a voice actor to read in a target style.

Amazon’s AI model consists of two components. The first is a generative neural network that converts a sequence of phonemes into a sequence of spectrograms, or visual representations of the spectrum of frequencies of sound as they vary with time. The second is a vocoder that converts those spectrograms into a continuous audio signal.

The end result? An AI model-training method that combines a large amount of neutral-style speech data with only a few hours of supplementary data in the desired style, and an AI system capable of distinguishing elements of speech both independent of a speaking style and unique to that style. Amazon has used it internally to produce new voices for Alexa, as well as developer-facing voices across several languages in Amazon Polly.

Finally, Amazon says that developers can use 10 additional Amazon Polly voices in 6 new languages, including U.S. English, U.S. Spanish, Canadian French, Brazillian Portuguese, and more.

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Big Data – VentureBeat

6 Skills You Need to Become a Data Science Superhero

April 9, 2020 TIBCO Spotfire

Reading Time: 2 minutes

Just in the last half a decade, there has been a 344 percent increase in demand for data scientists. But since the workforce can’t automatically shift to meet this demand, there was a shortage of nearly 150,000 data scientists last year.

Despite the fact that demand for data scientists outstrips supply, the field is still extremely competitive as data scientists clamor for the top positions. To be more valuable to companies and earn these positions, a plethora of skills are needed.

Below are the top six skills, consistent across the industry, that you need to focus on in order to develop your inner data science superhero.

Captain Obvious: Develop Python Skills. Almost every data science project could be improved with Python scripting. When looking at employing data scientists, the top desired skill is Python. While there are many open source languages available today, Python consistently takes first place across the data science industry.
Agent Collaboration: Develop People Skills. Often overlooked, people skills for data scientists are critical. With more and more citizen data scientists and business users getting involved in data science projects, having business acumen and good communication skills, playing well with others, and building trust and engagement is critical for a data scientist.
The Incredible Scaler: Develop Your Ability to Scale. Innovative companies today are racing to scale with data science, AI, and ML. But there are several barriers you must overcome first, including DevOps considerations, implementing a low-code/no-code analytics environment, balancing open source with an ability to scale, and infusing analytics into the business for real value.
Doctor Data: Develop Your Inner Data Engineer. Wonderful data scientists make raw data enterprise ready with data engineering. That means showing expertise in data prep, federation and virtualization technologies, SQL, and master data management and reference data management.
Ethos: Keep Ethics in Mind. Remember, just because you can do something does not mean you should do something. With these new data science superpowers, comes great responsibility to consider ethics, privacy, and regulatory issues in your work.
Vog: Learn to Soar in the Cloud. Fluency in the diversity of cloud computing solutions available today can bring great value to organizations today. Make sure you consider the following in any cloud computing project: ensure your cloud instance meets the business requirements you are looking to fill, think about cross-cloud compatibility, and the possibility of hybrid cloud environments.

Do not become too comfortable being a data scientist. With the demand that we are experiencing it is an easy trap. By focusing your time and effort on a few key areas, you will develop your inner data science superhero and maintain relevance in this competitive and rewarding career.

This was just an overview of the skills, make sure to watch the full webinar to gain more insight into why these areas are so valuable and details on how to up your game.

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The TIBCO Blog

MIT CSAIL’s VISTA autonomous vehicles simulator transfers skills learned to the real world

March 24, 2020 Big Data

In a recent study, researchers hailing from MIT’s Computer Science and Artificial Intelligence Laboratory and the Toyota Research Institute describe Virtual Image Synthesis and Transformation for Autonomy (VISTA), an autonomous vehicle development platform that uses a real-world data set to synthesize viewpoints from trajectories a car could take. While driverless car companies including Waymo, Uber, Cruise, Aurora, and others use simulation environments to train the AI underpinning their real-world cars, MIT claims its system is one of the few that doesn’t require humans to manually add road markings, lanes, trees, physics models, and more. That could dramatically speed up autonomous vehicle testing and deployment.

As the researchers explain, VISTA rewards virtual cars for the distance they travel without crashing so that they’re “motivated” to learn to navigate various situations, including regaining control after swerving between lanes. VISTA is data-driven, meaning that it synthesizes from real data trajectories consistent with road appearance, as well as distance and motion of all objects in the scene. This prevents mismatches between what’s learned in simulation and how the cars operate in the real world.

To train VISTA, the researchers collected video data from a human driving down a few roads; for each frame, VISTA predicted every pixel into a type of 3D point cloud. Then, they placed a virtual vehicle inside of the environment and rigged it so that when it made a steering command, VISTA synthesized a new trajectory through the point cloud based on the steering curve and the vehicle’s orientation and velocity.

VISTA used the above-mentioned trajectory to render a photorealistic scene, estimating a depth map containing information relating to the distance of objects from the vehicle’s viewpoint. By combining the depth map with a technique that estimates the camera’s orientation within a 3D scene, the engine pinpointed the vehicle’s location and relative distance from everything within the virtual simulator, while reorienting the original pixels to recreate a representation of the world from the vehicle’s new viewpoint.

In tests conducted after 10 to 15 hours of training during which the virtual car drove 10,000 kilometers (0.62 miles), a car trained with the VISTA simulator was able to navigate through previously unseen streets. Even when positioned at off-road orientations that mimicked various near-crash situations, such as being half off the road or into another lane, the car successfully recovered back into a safe driving trajectory within a few seconds.

In the future, the research team hopes to simulate all types of road conditions from a single driving trajectory, such as night and day, and sunny and rainy weather. They also hope to simulate more complex interactions with other vehicles on the road.

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Big Data – VentureBeat

Microsoft kills all third-party skills as it refocuses Cortana for the enterprise

February 29, 2020 Big Data

Microsoft today announced plans to streamline Cortana, its cross-platform virtual assistant, in future versions of Windows 10. A chat-based UI with support for both voice and keyboard will arrive in the next release, as well as features that let users check their calendars, set reminders, and perform other productivity-related tasks. At the same time, Microsoft says that it’ll remove music, connected home, and third-party Cortana app integrations as it “tightens access” on work and school accounts, and that it’ll end support for Cortana in older versions of Windows “that have reached their end-of-service dates.”

“We’re excited about how these updates to Cortana will help you stay on top of things, save time and do your best work. As we continue to innovate on Cortana … we plan to share further improvements in the coming months,” wrote Cortana corporate vice president Andrew Shuman in a blog post.

Beyond the new chat-based UI, the improved Cortana will recognize commands like “Tell me what’s next on my calendar,” “Remind me to send the ‘weekly report’ every Friday at 2 p.m.,” “Add ‘status report’ to my task list,” and others in the same vein. English-speaking users in the U.S. will see improved people-, email-, and file-finding capabilities and in-person meeting insights, but international users won’t be so lucky. Those in non-U.S. markets will initially be limited to Bing Answers and basic Cortana conversations.

Here’s the full list of soon-to-be-available skills, as per a Microsoft spokesperson:

Calendar
Join My Meeting
Reminders
Lists
Assistant Conversations/Chit Chat
Bing Answers
Alarms
Timer
Open Apps
Open Settings
People search
Media controls like “turn up the volume”

Microsoft says it plans to remove all Cortana skills and integrations that aren’t on the above list, but that it will “continually be adding additional functionality to the experience.”

Elsewhere, using Cortana in Microsoft 365 (Microsoft’s line of subscription services offered by Microsoft as part of the Microsoft Office product line) will require signing into a Microsoft account going forward. Microsoft also says it plans to turn off the Cortana services in Microsoft Launcher, its home screen experience for Android, by the end of April (as previously announced).

“This is all part of Cortana’s evolution into a personal productivity assistant. These productivity capabilities will be most beneficial to our commercial … customers,” the spokesperson told VentureBeat. “We look forward to adding additional functionality soon, and based on customer feedback will continue to evolve the experience.”

The changes come as Microsoft refocuses Cortana for the enterprise — specifically for Windows and Office customers. The assistant recently gained the ability to read email summaries and send quick-reply response in Outlook, and to schedule meetings and to deliver daily schedules and task rundowns. Email briefings from Cortana in Outlook can now suggest optimal focus times, and last year, Microsoft launched Presenter Coach, a PowerPoint service that listens to your presentations and then provides feedback on pace, use of inclusive language, and repetitive use of mannerisms like “umm” and “basically.”

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Big Data – VentureBeat

Amazon’s Alexa Knowledge Skills enables voice-guided FAQs, glossaries, and more

December 16, 2019 Big Data

In yet another step toward the enterprise side of the burgeoning conversational intelligence segment, Amazon today launched Alexa Knowledge Skills, a new skill type for its Alexa platform that allows employees and customers to ask questions about an organization’s data without invoking a skill name. It’s available in preview starting today, ahead of general availability in the months to come.

As Alexa senior product marketing manager Ben Grossman explains in a blog post, Alexa Knowledge Skills enable folks to ask Alexa about different types of data, including (but not limited to) organization charts, building information, events, FAQs, glossaries, product catalogs, and more. Developing such a skill requires a spreadsheet of data but no extensive coding or cloud infrastructure, and the skills are privately distributed through Amazon’s Alexa for Business or Alexa for Hospitality services, meaning that they remain accessible only on devices within an organization.

Knowledge skills enable Q&A on spreadsheet data that developers upload and map to templates. These templates correspond to different use cases, like How To (“Alexa, how do I log on to the Wi-Fi?“), Events (“Alexa, when is the next keynote?“), In-Store Assistant (“Alexa, where can I find the pasta?“), and others.

Developers who opt to use the People Directory template for their Knowledge skill can answer questions like these, as well as many others:

Single fact — “Alexa, when did Mary Major start?”
Multiple facts — “Alexa, what’s John Public’s start date and phone number?”
Counts — “Alexa, how many software developers are in New York?”
Lists — “Alexa, what employees are located in New York?”
Statistics — “Alexa, what’s the average tenure for software developers?”
Superlatives — “Alexa, who are the newest employees in New York?”
Reasoning –- “Alexa, is Jane Doe a software developer?”

Amazon says that already, organizations including BayCare Health System and Saint Louis University are developing Knowledge skills to help students and hospital visitors find campus places and resources. “Alexa Knowledge skills bring BayCare the opportunity to customize the Alexa experience across the health system without the need for complex coding and lengthy development processes,” said BayCare Health System director of innovation Craig Anderson. “We see massive potential at our 15 hospitals, BayCare’s many outpatient centers, and our HealthHubs to deliver answers in real time directly to our customers and Team Members via Alexa.”

To start creating a Knowledge skill, head to the Alexa developer portal and log in with an Alexa developer account. Then, choose the “Knowledge” skill type, and within the Knowledge skill interface, add templates to the skill before downloading a preformatted spreadsheet for each template. Add data to the spreadsheet and upload it to the skill, and then review and test the example queries Alexa automatically generates based on the data.

Alexa Knowledge Skills build on Amazon’s previous enterprise forays. Alexa for Business and Alexa for Business Blueprints allow employees to schedule meeting rooms (with third-party services such as Cisco, Polycom, Zoom), share itinerary information (through Concur), check voicemail messages, and quickly see if meeting rooms are available, and they enable admins to control users’ capabilities through a web dashboard and publish private skills from preconfigured templates. As for Alexa for Hospitality, it lets guests at hotels and resorts ask Alexa for specific information, such as pool hours, as well as order room service, control smart devices and appliances, access their personal music and audiobook libraries, and ask the concierge for dinner recommendations using just their voice.

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Big Data – VentureBeat

Infinite Skills Create Miracles

September 12, 2019 SAP

Many chemical companies are trying to cope with growing B2B customer demand. Some are responding by running trial-and-error approaches; others are applying a more conservative, academic method; and still others are waiting and watching what the competition is coming up with. “If it works for them, we can simply adopt it in our business,” they think. In reality, adopting other companies’ approaches isn’t the best idea.

In times like these, when technology offerings are so broad that you can spend ages evaluating them, it’s a good idea to discuss best practices. Chemical companies can leverage their networks to exchange knowledge and experiences. However, the steps of progress are small, and success often is very limited.

I see three major topics that I believe are preventing companies from coming up with the miracles they want.

1. Focusing on isolated tools

Complex spreadsheets are not digitalization, just like an app is not digitalization. Many projects are heavily isolated by technology, the IT organization, the business, or other factors that prevent them from delivering a true user- and customer-centric service, one where the user says, “Thank you!” instead of, “Pheww, I survived this!”

Magic moments, in the context of customers and their journeys, are created from a bigger picture that measures success way beyond implementation and costs.

2. Being too comfortable in your comfort zone

There is a good reason why a comfort zone is hard to leave – it is comfortable!

You have probably heard of design thinking and other creative methods to boost innovation or improve business models. Ideally, these workshops include many people with different perspectives, although some people (notably scientists) have a hard time with the process. My recommendation: Trust the process.

Statements and thought patterns like “We tried this years ago, it did not work!” or “It is not supported by the process!” are not allowed in design thinking workshops (at least not in ones I’m leading). I see many companies investing a lot of time in these workshops without a real willingness to evaluate the outcome. They may have limited resources to drive the process, or they may fear setting unrealistic customer expectations, or they may simply misunderstand concepts like prototyping or minimum viable project. This usually this ends with an over-engineered, “more of the same,” expensive, and process-oriented solution that doesn’t solve any problems for the target group.

“Most of the executives I talk to are still very much focused on digital largely as a way to do ‘more of the same,’ just more efficiently, quickly, and cost-effectively. But I don’t see a lot of evidence of fundamentally stepping back and rethinking, at a basic level, ‘What business are we really in?’”

– John Hagel III, co-chairman of Deloitte LLP Center for the Edge

3. Missing skills

Worse than knowing you don’t have the right skills is not knowing what skills you need.

Many years ago, I was having a dialogue with a colleague from R&D. He told me he was struggling to fill some open positions for chemists. As we talked, I realized he was not just looking for chemists but for chemists with an IT background.

Fortunately, he knew what he was looking for, but many others do not see the need to change their employee profiles to find the right resources. This puts more work on your staff’s shoulders without solving your problems. Also consider that certain countries and regions may require a set of skills that you haven’t heard of before. Your local business operation can help you develop these profiles.

The success of your business starts with the skills and the empathy of your employees.

Summary

Always look for the big picture, ask yourself why something is relevant, and think about the journey of your target group. Think about measuring success from their point of view, not your own. Identify the blind spots in your service, improve your employees’ skills, and teach them to identify with the success they are generating, not just the job they’re doing. Find a partner who helps you gain a different, more challenging perspective.

Discover how packaged tools and services help your organization with a successful migration to SAP S/4HANA in our Webinar series on the SAP S/4HANA Movement program.

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Digitalist Magazine

The Top Skills You Need To Lead In Times Of Continuous Change

May 25, 2019 BI News and Info

In times of digital transformation, change has become a constant. Guiding companies through their business transformation journey not only requires creating more agile organizational structures and processes, it also demands instilling cultural change. Business leaders need to transform their organization into an intelligent enterprise, rooted in a corporate culture that thrives on continuous change.

The transformation has to start from the heart of the organization. One of the most striking results in the 22nd Annual Global CEO Survey by PwC was that organizations are turning inward to drive revenue growth in an unpredictable international socio-economic environment. They are focusing on strengthening the organization’s digital core, closing capabilities gaps, and improving organizational efficiencies.

Embracing constant change at work does not happen overnight. It requires shifting mindsets and behavioral patterns. Here are the key leadership skills that help business and IT executives succeed.

Practice active listening

The number one priority in transformation processes is active listening. Organizational change can be unsettling. A work routine offers predictability. Changing job requirements demand leaving a familiar comfort zone. Listening can help to calm fears, recognize opportunities, and embrace a new style of work. While comfort zones can be reassuring, they are also confining and the nemesis of professional growth. Dedicate time to meet with individual teams to listen to their challenges, insights, goals, and ideas. Active listening helps identify the gaps between where we are and where we want to go as a team. These gaps are opportunities for growth for team members. Active listening helps the team become comfortable with being uncomfortable as a driver of change and renewal.

Create a networked organization

One of the top priorities for business transformation is to accelerate the speed of innovation and create a new dynamic within the organization that allows every employee to participate in the innovation process. Similar to the way daily work routines can confine growth opportunities, keeping collaboration within defined organizational structures can also curb innovation capabilities. Approaches like design thinking help business leaders create a network organization with the potential to engage employees across the organization for the development of new products and services. A networked organization opens ups opportunities for teams to collaborate beyond the traditional mindsets and organizational boundaries.

According to Prof. Uli Weinberg and Dr. Claudia Nicolai, who teach design thinking at the Hasso-Plattner-Institute, “design thinking is creating innovation opportunities (within and across the organization) and is a leading principle of change of transformation. The organizational structure of a network offers new, dynamic ways of acting and reacting timely and efficiently – on an intra-organizational as well as on an inter-organizational level.”

Provide a North Star

Leading in an interconnected work environment with flexible processes and fluid teams requires striking a delicate balance between encouraging creativity and maintaining focus. Steering organizations through change is most successful when a clear purpose is the North Star, as it serves as an inspiration and compass for the team. Not having a purpose as the guiding force can be dire. The Global Leadership Forecast 2018 (published by EY, The Conference Board, and DDI) concluded that organizations that operated without a purpose-driven culture, or even a purpose statement, financially underperformed the average by 42%.

Last but not least, leading through change requires having the trust from the team to take the leap with you, or as Seth Godin recommends, “earn trust, earn trust, earn trust. Then you can worry about the rest.”

Invest in employee well-being to drive optimal results for your growing business. Read the SAP white paper “Creating Resilient Cultures: Why Businesses Need to Invest in Employee Well-Being.”

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Digitalist Magazine

Microsoft releases Windows Vision Skills preview to streamline computer vision development

May 1, 2019 Big Data

Computer vision is an exceedingly useful subfield of machine learning that’s been applied to everything from facial recognition to tuberculosis diagnosis, and Microsoft wants to streamline its deployment on Windows. The company today released a preview of Windows Vision Skills, a set of packages that enable a range of AI-driven photo and video analysis tasks.

Three prebuilt skills are available at launch: Object Detector, Skeletal Detector, and Emotion Recognizer.

“Implementing and integrating efficient machine learning and computer vision solutions is a hard task for developers. The industry is moving at a fast pace, and the amount of custom-tailored solutions coming out makes it strenuous for application developers to keep up,” wrote Microsoft developer writer Eliot Cowley in an article. “The Windows Vision Skills framework is meant to make it easier to utilize computer vision. It standardizes the way computer vision modules are put to use within a Windows application, running on the local device.”

Developers can add the skills — modular bits of code that process inputs and produce outputs — to any .NET, Win32, and UWP application courtesy out-of-the-box WinRT APIs that don’t require prior machine learning or computer vision knowledge to use. Meanwhile, computer vision developers can take advantage of hardware acceleration frameworks like DirectX and DirectML on Windows devices by packaging their solutions as skills.

Microsoft says that the Windows Vision Skills framework can be extended to work with existing machine learning frameworks and libraries such as OpenCV, and it says that skills can be pieced together within an application to address a complex scenario or bundled together in a single package.

Windows Vision Skills complements existing Windows support for inference of ONNX models by utilizing WinML for local inferencing. The framework allows you to build intelligent applications while leveraging platform optimization.

“Skills are strongly versioned to ease iteration without breaking existing applications,” said Cowley, “[and they’re] easy to ingest, easy to update, and they preserve intellectual property through licensing.”

Microsoft isn’t the only company that’s made computer vision tools available in open source recently. Last week, Google debuted AI image segmentation models optimized for its Cloud TPU hardware platform, and in March, Intel made generally available CVAT, a toolkit for image data labeling. Last March saw the launch of Intel’s OpenVINO, a computer vision toolkit for edge computing that’s compatible with open source frameworks like Facebook’s Caffe2 and Google’s TensorFlow. And two years ago, Facebook rolled out a trio of tools for segmenting objects within images.

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Big Data – VentureBeat

Tag Archives: skills

Invest Your Time in the Right Skills to Become a Data Scientist in 2021

How to get started and gain experience?

What kinds of hands-on experience do you need?

What technical skills need to be part of your resume?

How to find a job?

TIBCO4Good and She Loves Data Offer Free Data Skills Workshops During a Time of Vulnerability

Back on Your Feet Program: Empowering Individuals Impacted by the Pandemic

Program Benefits and Session Structure

Amazon releases long-form speaking style for Alexa skills

6 Skills You Need to Become a Data Science Superhero

MIT CSAIL’s VISTA autonomous vehicles simulator transfers skills learned to the real world

Microsoft kills all third-party skills as it refocuses Cortana for the enterprise

Amazon’s Alexa Knowledge Skills enables voice-guided FAQs, glossaries, and more

Infinite Skills Create Miracles

1. Focusing on isolated tools

2. Being too comfortable in your comfort zone

3. Missing skills

Summary

The Top Skills You Need To Lead In Times Of Continuous Change

Practice active listening

Create a networked organization

Provide a North Star

Microsoft releases Windows Vision Skills preview to streamline computer vision development

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