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Machine Learning

Is the cloud the key to democratizing AI?

These days, AI is expected to drive worldwide revenues from nearly $8 billion in 2016 to more than $47 billion in 2020, across a broad range of industries. There is no doubt that AI has changed the way we run business.

Take a case of Makoto Koike as an example. It takes his mother 8 hours each day to sort cucumbers from the family farm into different categories at the peak of the Japanese harvest. This is such a boring, time-wasting task that he finally made a decision to using automation. Makoto started off with TensorFlow, a popular open-source machine learning framework Despite not being a machine learning expert. Sorting by size, shape and other attributes, the system has an accuracy rate of around 75 %. This proved how AI could transform even the smallest family-run business sooner or later.

How does machine learning work? All you need to know

Many of us may hear about machine learning before. However, you might not have the full understandings of the way it works. Today we will discuss this topic in more details.

Machine learning can be the modern science which gets computers the ability to act, but they can be explicitly programmed. Previously, it gave us a throughout understanding of our human genome, self-driving cars, effective web search, and practical speech recognition. Nowadays, machine learning can be so pervasive that you can use it several times per day without having full knowledge about it. Also, many researchers think this can be the critical way for the human to make the significant progress towards AI at the human level.

How does machine learning work?

To obtain the most valuable result from methods of machine learning, we might need to know the way to pair its best algorithms and let them fit the right processes and tools. SAS comprises sophisticated, rich heritage in term of statistics as well as data mining which comes along with new advances regarding the architecture to ensure the models run at its fastest speed – even in the huge and complex enterprise environments.

What are some popular machine learning methods?

Meta Description: there are several machine learning methods. Of which, unsupervised learning and supervised learning are two widely adopted methods we may all know. Let’s look at the overview of some popular machine learning methods.

All you need to know about machine learning methods

What is supervised learning?

As far as you may know, algorithms of supervised learning are educated using some labeled examples, like an input without knowing its desired output. In more details, a piece of equipment may have many data points with the “R” (runs) or “F” (failed) labels. This learning algorithm may receive all inputs came along with its corresponding outputs. In this way, such algorithm learns a lot by comparing the actual output of this method with all correct outputs in order to find as many errors as possible. Then, it modifies the machine learning model accordingly.

An Ultimate Guide to Machine Learning

Meta Description: With the computing technologies, there are more and more people know about machine learning today. Its iterative aspect is indeed vital as models can be exposed directly to new information and data before adapting independently.

What is Machine learning?

Machine learning can be known as a data analysis method which automates analytical building model. It is also an artificial intelligence branch and was built from the basis that systems may learn much from data, then identify patterns before making decisions with the minimal intervention of the human.

This definition was first introduced from the theory that computers may be enabled to learn to perform different tasks without any accompanying programs and pattern recognition. For researchers of artificial intelligence, their main expectation is the desire to see whether computers can learn well from data. Such computers gain knowledge from their previous computations in order to produce repeatable, reliable results and decisions. It is not a new science, but it gained the fresh momentum.

What do you know about its basics

While many algorithms of machine learning have stayed healthy for a while, their ability to apply complex calculations of mathematics automatically to the big data faster and longer is a new development. Let’s look at a few publicized examples regarding applications of machine learning you may want to consider:

How to get started with AI – before it’s too late

These days, Artificial Intelligence is becoming more popular because of capability and influence at an astonishing rate across virtually every industry. Yet the speed and scale of AI is such that some long-standing norms are facing disruption. In this article, we would show you 5 ways  to explore what each of us can do to prepare for this bold new future and make the most of AI.

1. Make yourself  an AI expert 

Recently, many people believe that it will take too long to learn it yourself. But these are early days. Thanks to the development of the Internet, AI becomes the biggest opportunity; it’s just getting started. Relying on your computer science and math expertise, you’ll want to brush up on the following:
  1. Statistics
  2. Calculus
  3. Linear algebra
  4. Algorithms
  5. Convex optimization
  6. Graph theory
  7. Current programming tools and trends
  8. Data analysis
To begin with, you should grasp practical skills helping you understand machine learning at a low level. Here they are:
  1. Data wrangling
  2. Cross validation
  3. Distributed computing
  4. Data visualization
  5. Database management
  6. Feature engineering
In addition, if you are processing your big data set to choose features and explore its statistical properties, R would be a great tool to familiarize yourself with. An ideal way to get up to speed on these subjects are Data science bootcamps like The Data Incubator and Zipfian Academy. Also, it’s noticeable that the exact role and necessary skill set of a data scientist varies depended on the problem they’re attempting to solve.

Machine learning experience for computer engineers

Robert Heinlein published a book called "A Door into summer" in the mid-1950. In his book, skilled mechanical engineer hooked up some "Thorsen hoses" for pattern matching memory and some "side circuits to include decision making" and generated an entire industry of intelligent robots. In other to make the story more imaginable, in 1970 it was set well into the future. These robots are involved in tasks like washing dish illustrated to them and then repeat the process entirely. 

I don’t think I have to inform you, but it didn't happen in the right way. It may have seemed believable in 1956, but in 1969 it was apparent that it wouldn't turn out in 1970. Every ten years the capability for an average engineer to build a synthetically intelligent machine seemed to be impossible as time passed. As technology gets better, the enormous complexity of the problem became evident as different layers of complexity were discovered.

What is machine learning ?

You must have heard about machine learning many times lately. It is also known as artificial intelligence; machine learning is a division of AI, both can be traced with their sources from MIT in the 1950s.

Machine learning is usually encountered every day, whether you believe it or not. The technology that maintains self-driving cars from crashing into things, Alexa and Siri voice assistants, Amazon and Netflix recommendations and Facebook’s and Microsoft’s facial detection all are results of advances in machine learning.

iOS 11 is coming with machine learning

The latest iOS launch is less than a few weeks now. Many iPhone users are restlessly waiting for Apple’s recent improvements, and the pressure is much on the developers to meet up with the hype. The most important thing these final weeks is coming down on the iOS updates that signify a basic shift in how customers interact with mobile apps. As organizations plan to make a change in the iOS market this coming September, the time is now focused on the high-bets modifications that will have the most impressive impact on consumers.

With the help of latest machine learning abilities around location, visuals, language, and gaming incorporated into the iOS 11 platform, while AI-driven apps are in the outlook. Apple depends on developers to offer iOS advancement to the next stage and users depend on these changes when they update their iPhones.

This is the time to deep learning in the cloud

The AWS Re-invent conference is far approaching, and there are many predictions in Amazon Web Services that will be announced soon. It is certain that it will announce some in-depth learning cloud service. For sure, Microsoft, IBM, and Google will not be left behind. Also, both Microsoft and IBM have their personal unique deep learning projects in the works known as Distributed Deep Learning and Brainwave, respectively.

Thus, what is the difference between deep learning and machine learning? Deep learning offers a foundation for understanding vast amounts of data or patterns. Machine learning deals with strategic applications of AI, such as making direct predictions.

Machine Learning and Deep Learning In The Cloud: Are You Ready?

Artificial Intelligence and Deep learning in the Cloud are believed to change the world one day, thanks to the massive Cloud Computing technology power.

For a long time, enterprises have decided to dip a toe into the artificial intelligence, going first with machine learning. However, until today, the demand for such data turns out to be quite in a rush to keep a competitive edge. Therefore, it’s best to learn how his classic machine learning has developed from deep learning based on the great power of cloud computing. And it’s true that deep learning systems have grown up considerably, but have you wonder if these tools are all ready to bring out any business?

Machine learning and deep learning teach humans how to learn and do tasks 

A lot of manufacturing firms, for example, have utilized classic machine learning for maintenance and identify tool failure, allowing the technicians to solve possible issues. However, such out-of-date systems as compared with what is done today, availing more advanced algorithms that make use of the modern computing power.

How to notice if machine learning or AI is real

Gradually it seems that all application and cloud service has been equipped with artificial intelligence and machine learning. Presto! They can now perform different magic.

Most of the marketing tactics around AI and machine learning is deceptive, making false promises and listing the terms they don’t apply. In other words, many BS are being marketed. Make sure that you do not fall for those snow jobs.

Before I discuss how you can check if the software or service uses AI or machine learning, let me explain the meaning of those terms:

Role Of Cloud System In Democratizing Machine Learning

What do you know about Artificial Intelligence? How to democratize it? Keep reading my article.


It is undeniable that Artificial Intelligence has played an important part in our daily life, especially in the modern machine learning. However, how to democratize it tends to be still a hard question for many IT users. A lot of IT specialists think that the connection between Artificial Intelligence and the cloud can democratize Artificial Intelligence. My today article will help you insight into this issue.

Background of Artificial Intelligence

Admittedly, how Artificial Intelligence will be used effectively and exclusively in business appears to be a burning question to many people. Regardless of what the answer is, I am sure that Artificial Intelligence sooner or later will replace a large number of workers as well as staffs in companies. Therefore, it is high time for us to prepare for this significant change in the modern machine learning.

Nowadays there are two choices for you to make when you decide to pick a cloud database. You have to determine that your cloud database is run on cloud only or premises.

Machine Learning In The Modern Technology

Have you ever heard about machine learning? How to apply it to our today applications? My article will answer these questions.

It is a norm that many people misunderstand the machine learning is just applied to a cloud system. However, the modern technology world always changes in such a short time, even a minute. In recent times, Microsoft, the largest computer controlling corporation in the world, has announced to incorporate machine learning into its PC for the next Windows 10. Of course, we need good preparation for this significant change. I think my today article will help you understand more about this topic.

It is not a long time for the release of Windows 10 at present. Apparently, I am sure that Microsoft Corporation will show its new applications in all ranges and fields, especially new APIs for computers and smartphones.

Why will machine learning become a promising marketing tool?

Have you ever heard of machine learning? What do you know about it? How can it help us on the market? Keep reading my today article.

At present, machine learning seems to be a new term on business and market to many people. However, I think in the near future, machine learning will gradually dominate our modern market thanks to its superior features. There is no doubt that nowadays businessmen take advantage of different tools in expanding their market. And, to some extent, machine learning still has a moderate position in this area. Nevertheless, I strongly believe that this method will certainly replace others to be a preferred tool on the future market. To help you understand more about machine learning as well as its potential in the near future, I show you 5 plausible reasons explaining why machine learning can become the future of marketing.

How Do Big Data And Machine Learning Help Companies?

What do you know about big data and machine learning? How can they help us? Keep reading my today article.

It is undeniable that in our modern technology, machine learning, and big data have gradually been an indispensable part. In the near future, I think that these above Artificial Intelligence products will dominate all structures in technology. Of course, when machine learning cooperates with big data, it will bring surprising effects in tackling different complicated issues. My today article will help you insight into this field.

Background of big data and machine learning

There is no doubt that combining big data and machine learning is very important in the modern technology. They also bring a lot of opportunities for businessmen.

What should we prepare for AI in the machine learning era?

What do you know about Artificial Intelligence? How to prepare for this significant change in machine learning? Keep reading this article.


AI has been a familiar technical term in our modern lives in recent years. There is no doubt that Artificial Intelligence is applied in various different fields and will play an indispensable role in the near future.

Admittedly, how Artificial Intelligence will be used effectively and exclusively in business appears to be a burning question to many people. Regardless of what the answer is, I am sure that Artificial Intelligence sooner or later will replace a large number of workers as well as staffs in companies. Therefore, it is high time for us to prepare for this significant change in the modern machine learning.

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