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The amount of data generated on a day-to-day basis is humungous so much so that the term given to identify such a large volume of data is coined as big data. Big data is usually raw and cannot be used to meet business objectives. Thus, transforming this data into a form that is easy to understand is important. This is exactly where machine learning comes into play. With machine learning in place, it is possible to understand the customer demands, their behavioral pattern and a lot more thereby enabling the business to meet its objectives. For this very purpose, companies and experts rely on certain machine learning tools. Here is our find of top machine learning tools used by experts in 2021. Have a look!

Keras is a free and open-source Python library popularly used for machine learning. Designed by Google engineer Franois Chollet, Keras acts as an interface for the TensorFlow library. In addition to being user-friendly, this machine learning tool is quick, easy and runs on both CPU and GPU. Keras is written in Python language and functions as an API for neural networks.

Yet another widely used machine learning tool across the globe is KNIME. It is easy to learn, free and ideal for data reporting, analytics, and integration platforms. One of the many remarkable features of this machine learning tool is that it can integrate codes of programming languages like Java, JavaScript, R, Python, C, and C++.

WEKA, designed at the University of Waikato, in New Zealand is a tried-and-tested solution for open-source machine learning. This machine learning tool is considered ideal for research, teaching I models, and creating powerful applications. This is written in Java and supports platforms like Linux, Mac OS, Windows. It is extensively used for teaching and research purposes and also for industrial applications for the sole reason that the algorithms employed are easy to understand.

Shogun, an open-source and free-to-use software library for machine learning is quite easily accessible for businesses of all backgrounds and sizes. Shoguns solution is entirely in C++. One can access it in other development languages, including R, Python, Ruby, Scala, and more. Everything from regression and classification to Hidden Markov models, this machine learning tool has got you covered.

If you are a beginner then there cannot be a better machine learning tool to start with other than Rapid Miner. It is because of the fact that it doesnt require any programming skills in the first place. This machine learning tool is considered to be ideal for text mining, data preparation, and predictive analytics. Designed for business leaders, data scientists, and forward-thinking organisations, Rapid Miner surely has grabbed attention for all the right reasons.

TensorFlow is yet another machine learning tool that has gained immense popularity in no time. This open-source framework blends both neural network models with other machine learning strategies. With its ability to run on both CPU as well as GPU, TensorFlow has managed to make it to the list of favourite machine learning tools.

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Top Machine Learning Tools Used By Experts In 2021 - Analytics Insight

Calling all data devotees, machine-learning mavens and arbiters of AI. Clear your calendar to make room for the iMerit ML DataOps Summit on December 2, 2021. Join and engage with AI and ML leaders from multiple tech industries, including autonomous mobility, healthcare AI, technology and geospatial to name just a few.

Attend for free: Theres nothing wrong with your vision the iMerit ML DataOps Summit is 100% free, but you must register here to attend.

The summit is in partnership with iMerit, a leading AI data solutions company providing high-quality data across computer vision, natural language processing and content that powers machine learning and artificial intelligence applications. So, what can you expect at this free event?

Great topics require great speakers, and well have those in abundance. Lets highlight just three of the many AI and ML experts who will take the virtual stage.

Radha Basu: The founder and CEO of iMerit leads an inclusive, global workforce of more than 5,300 people 80% of whom come from underserved communities and 54% of whom are women. Basu has raised $23.5 million from investors, led the company to impressive revenue heights and has earned a long list of business achievements, awards and accolades.

Hussein Mehanna: Currently the head of Artificial Intelligence and Machine Learning at Cruise, Mehanna has spent more than 15 years successfully building and leading AI teams at Fortune 500 companies. He led the Cloud AI Platform organization at Google and co-founded the Applied Machine Learning group at Facebook, where his team added billions of revenue dollars.

DJ Patil: The former U.S. Chief Data Scientist, White House Office of Science and Technology Policy, Patils experience in data science and technology runs deep. He has held high-level leadership positions at RelateIQ, Greylock Partners, Color Labs, LinkedIn and eBay.

The iMerit ML DataOps Summit takes place on December 2, 2021. If your business involves data-, AI- and ML-driven technologies, this event is made for you. Learn, network and stay current with this fast-paced sector and do it for free. All you need to do is register. Start clicking.

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A look at some of the AI and ML expert speakers at the iMerit ML DataOps Summit - TechCrunch

Artificial intelligence and machine learning capacities are allowing analysts to produce quicker, more streamlined assessments.

Americas national security organizations have begun applying AI to more quickly and effectively produce intelligence assessments.

Speaking at the GovernmentCIO Media & Research AI: National Security virtual event, Director of the National Security Agency (NSA) Research Directorate Mark Segal discussed how these new capacities are assisting intelligence analysts in better processing and sorting large quantities of often complex and disparate information.

In outlining the NSAs research priorities, Segal noted that both AI and machine-learning capacities already showed promise for better organizing the large pools of variable data their analysts sort through in producing regular assessments.

One of the challenges that we have found AI to be particularly useful for is looking through the sheer amount of data that's created every day on this planet. Our analysts are looking at some of this data trying to understand it, and understand what its implications are for national security. The amount of data that we have to sort is going up pretty dramatically, but the number of people that we have who are actually looking at this data is pretty constant. So we're constantly looking for tools and technologies to help our analysts more effectively go through huge piles of data, Segal said.

This application of AI to analysis has the potential to expedite the delivery of actionable intelligence to policymakers as well, who are able to more quickly and conclusively come to decisions based on a more effective sorting of available information.

We analyze information and then provide that analysis to policymakers. For example, lets say we're looking at a large pile of documents and trying to understand what the intentions of another country are by looking through that data quickly. We want to zoom in immediately on the most important parts of that data, and have our skilled analysts say, We think this entity is doing a specific thing, and then leave that to the policymakers to determine how we might respond, Segal said.

Segal cautioned that agency technologists need to start with a realistic understanding of AI and machine learning to make most effective use of these new capacities, and to see them in terms of how they can concretely refine internal processes and advance their organizations key aims.

One of the biggest risks about AI right now is that there's this huge amount of hype surrounding it AI is a tool just like any other tool. And the way that you use a tool is to figure out where it would be effective, and where it would actually help solve a problem in our research organization. One of the things that we try to do is actually look at the technology in order to apply it to real problems and analyze the results in a scientifically rigorous manner, Segal said.

Segal also cautioned agencies to avoid creating undue biases within their algorithms, as these built-in flaws would ultimately distort the resulting analysis in ways that are either ineffective or potentially dangerous if they go uncorrected.

A lot of machine-learning algorithms are trained on data, and one of the challenges that can emerge there is that if the data is biased, its going to affect the output," Segal said. "For example, with facial-recognition software, if the training data only has people that have a certain hair type, or a certain skin color, or certain facial features, it will not work in practice because when you encounter other data that you've not seen before, the algorithm will behave in unpredictable ways."

One of the most promising applications NSA researchers have begun exploring is automated data sorting, using AI to sift through large quantities of documents and identify relevant information far more quickly than a human worker would be able to.

Imagine you've got a very large pile of documents, and in some of these documents there are really important things you want analysts to look at while some of the other documents are completely irrelevant. So one of the ways that we've used AI and machine learning in particular is we can have a trained human look at a subset of these documents and train a model to say which ones are really important and which ones are less important. Once you've trained a model and have enough data that you train the model successfully, you can go through a much larger collection of documents much more quickly than a human being could do it, Segal said.

Another concrete use case that aligns AI with operational efficiency is using tailored algorithms to convert speech to text.

If you can do that, you can make that text searchable, which once again makes the analyst more productive. So instead of listening to thousands of hours of audio to hear one relevant audio clip, you put in a few keywords and scan all this processed text, Segal said.

Segal emphasized that no matter how advanced these capacities become, national security institutions should continue evaluating AI for both potential biases, as well as through the central criteria as to whether or not these new uses are conducive to their longstanding mission.

I think the main way that we do that is when we try these experiments, pilot studies and different techniques, we have a way of quantitatively measuring its effectiveness. When it proves to be effective, we refine the techniques. And when it proves not to be effective, we take a step back and think about why it failed, Segal said.

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AI Helping to Refine Intelligence Analysis - GovernmentCIO Media & Research

As we push forward into the future, it seems more and more certain that artificial intelligence and machine learning are going to be massive pieces of our collective future. Continuously producing and conceiving countless breakthroughs,new technologies, and industry-changing developments the world of AI and machine learning is rife with potential for new minds to help build and shape tomorrow. If you'd like to join the party, there's a lot to learn.

One way to dive deep into these pivotal technologies is to take advantage of this deal onThe Premium Machine Learning Artificial Intelligence Super Bundle, which is on sale for $36.99 (reg. $2,388). This nearly 80-hour collection of courses and lessons breaks down fundamental lessons on deep learning, machine learning, Python, and other development tools used to help grow these sections of the tech industry.

Upon subscribing and taking advantage of this incredible, you'll begin with Machine Learning with Python, which is a course that teaches you the fundamentals of machine learning with Python. In this practical, hands-on course you'll get the foundational lessons and examples on approaching data processing, linear regression, logistic regression, decision trees, and more. This course is taught by Juan E. Galvan, who is a top instructor, digital entrepreneur, and recipient of a 4.4/5 star instructor rating.

These are some of the other courses included in the attractive Premium Machine Learning Artificial Intelligence Super Bundle: The Machine Learning and Data Science Developer Certification Program, The Complete Machine Learning & Data Science with Python A-Z, and Deep Learning with Python. Each of these well-reviewed and well-curated courses will help you on your path to becoming an informed player in the growing world of AI and machine learning.

Don't miss your chance to grabThe Premium Machine Learning Artificial Intelligence Super Bundlefor only $36.99 (reg. $2,388).

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Dive Deep Into Machine Learning With Over 75 Hours Of Expert Led Training - IGN SOUTH EAST ASIA

Machine Learning to assist in addressing deferred care crisis

"Millions of Americans have gone without critical screenings and treatment for 18 months, creating a deferred care crisis that requires immediate and proven solutions to support those in need," said Gary Velasquez, CEO of Cogitativo. "We believe Visin will play a vital role in preventing acute medical events for vulnerable individuals and enabling health care organizations to mitigate many of the challenges that are on the horizon."

Cogitativo's new solution comes as health care payors and providers are reporting a rise in medical needs among individuals who were unable to receive care during the pandemic, including those with chronic conditions like cardiovascular disease, chronic kidney disease, diabetes, HIV, and mental health challenges. In addition, many providers are also struggling to manage a surge in patient visits, with the virus continuing to spread at the same time that people are returning to medical facilities for appointments, screenings, and treatment.

Visin analyzes patient health records through the lens of peer-reviewed literature on disease progression, social determinants of health, climate change, and other relevant data sources to predict elevated risk for an acute clinical event. These temporal-based predictions will enable healthcare payors and providers to identify members and patients most likely to require greater medical attention in the months ahead. This information will, in turn, facilitate health care payors and providers to proactively conduct outreach and render prophylactic care to at-risk beneficiaries and offer individualized recommendations on preventive care.

A version of Cogitativo's new machine learning platform was used by a host of health care leaders and public health officials during the pandemic. For example, Blue Shield of California used it to deliver personalized care and support to vulnerable beneficiaries; it helped guide mobile vaccination efforts in the City of Compton, California; and it provided insights to the U.S. Department of Health and Human Services.

"Visin is the field-tested machine learning tool that so many health care payors have been waiting for, and it cannot come soon enough for those managing the fallout from the deferred care crisis," said Dr. Terry Gilliland, Chief Science Officer at Cogitativo and former Executive Vice President of Health Care Quality and Affordability at Blue Shield of California.

"Cogitativo's new machine learning tool can help physicians throughout the country identify their highest-risk patients and conduct proactive outreach, providing those patients the critical care and attention they need while also preventing unpredictable waves of patient visits that create capacity problems," said Dr. Hector Flores, Director of the Family Care Specialists Medical Group. Dr. Flores used a version of Visin during the pandemic to support his most vulnerable patients.

About Cogitativo Inc.Cogitativo is a Berkeley-based data science company founded in 2015 with a mission to create and implement innovative, scalable solutions to the most complex challenges facing the healthcare system. Leveraging machine learning, proprietary data sets, and expertise from leaders with decades of experience working with public health agencies, Cogitativo can deliver actionable insights and save lives. To date, Cogitativo has successfully applied data science solutions to more than 200 unique operational challenges to significantly improve the efficiency of our healthcare systems and protect vulnerable patients and communities. Visitwww.cogitativo.comfor more information.

Media Contact:Joshua Rosen[emailprotected]Phone: (610) 2473482

Company Contact:Amy Domangue[emailprotected] Phone: (225) 337 -6402

SOURCE Cogitativo, Inc.

http://www.cogitativo.com

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Cogitativo Releases Visin, A First-Of-Its-Kind Machine Learning Tool Built to Tackle the Growing Deferred Care Crisis - PRNewswire