Machine learning

Machine learning (27)

Connect Your IoT Deployments to Machine Learning

As the number of internet-connected sensors continues growing due to increased applications in cars, planes, buildings, and home devices, businesses generate vast amounts of data. According to a study, there will be more than 50 billion IoT devices in the world by 2025. This is up from 9 billion in 2017. With this significant rise in data, tapping it to extract useful information is becoming a big challenge that traditional methods cannot meet. This is where machine learning (ML), one of the subsets of artificial intelligence (AI), comes into place.

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Things You Might Not Know About Machine Learning

Artificial Intelligence is already impacting the world in many ways. Many scientists have even compared it to the discovery of fire, although most of them differentiate the two on the creativity they need. While AI was a preserve of a few AI researchers and digital companies such as Google, Amazon, and Microsoft, that is no longer the case. AI has entered almost every industry, with nearly everyone now affected by this technology. Machine learning is one of the subsets of AI. It is based on algorithms that allow systems to learn on their own without relying on humans. 

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Machine Learning Is Creating a Global Shift

Artificial intelligence (AI) and Machine Learning (ML) are now considered some of the most groundbreaking inventions since the internet. We used to watch AI in movies and science fiction books, but it has now become a reality that we interact with in our daily lives. AI has become so famous to the extent that almost all technologies being invented today have some element of AI or machine learning. ML, a subset of AI, is an implementation of some abilities of humans. It enables people to carry out certain tasks by collaborating with smart software.

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Should We Trust Machine Learning Systems?

Machine learning systems are the crux of most of the major AI advances over the last decade.  Deep learning, the most advanced type of machine learning, has produced the computer vision systems that power self-driving cars, facial recognition systems, machine translation, speech recognition, and AI-based medical diagnosis systems.

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Machine Learning is Moving On in 2021

Although 2020 did not go exactly as expected, 2021 seems encouraging for many industries. For Machine Learning (ML) and Artificial Intelligence (AI) at large, experts predict that it will enter a golden age this year. With machine learning now top among the most sought after technologies, here is how machine learning will advance in 2021:

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How Is Machine Learning Changing?

 Machine learning (ML) is altering the landscape of all segments and industries such as education, transport, healthcare, and entertainment, among others. It will impact operations in other areas such as housing, shopping and cars. This technology is used in robotic process automation and making predictions that give business decision-makers insight regarding operations. As machine learning technology continues advancing, here are some trends that prove that it is changing:

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How Machine Learning May Change Education

Artificial Intelligence (AI) is now part of almost every industry. From parking systems to smart sensors, AI is promising to alter the way we do things through technologies such as computer vision and machine learning, and others. This technology provides tools that can be used to revolutionize education and training institutions. Its potential in this industry is enormous, ranging from robotic teachers, personalized learning, coaching using artificial intelligence, and automating administrative tasks in schools to reduce the cost of operations and enhance efficiency. Here are some ways in which machine learning may change education:

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Thinking that Machine Learning Isn't Making an Impact?

Artificial intelligence is a topic that we keep hearing now and then during discussions in different tech and business circles. Some people still associate it with science fiction movies, but the truth is, it is here with us and chances are, you might be interacting with it daily. The popular AI inventions include Siri and Alexa, both of which make our lives easy. These inventions have made AI a household name and Alexa is the evidence of its presence in our lives. While some people may see it as a new phenomenon, the concept is not new. It first came into existence as early as 1956, although it took decades to make progress towards making it a reality. Here are top AI and machine learning trends in 2021:

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Here's What's Coming in Machine Learning in 2021

Machine learning and artificial intelligence have been the leading topics of discussion in 2020. The coronavirus pandemic has made these technologies highly crucial than before, as they have shown the potential to help in many ways. Machine learning is now the driving force behind multi-billion industries such as medical diagnostics companies and autonomous vehicle companies, among others. With this immense potential, almost every industry is investing in it. Here are some trends that you should expect in 2021 going forward.

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Starting a Machine Learning Initiative?

Machine Learning and Artificial Intelligence (ML and AI) have become some of the most talked about technologies in the recent years. This has been occasioned by the prominence that these technologies have gained and the advancements in this area. As such, big tech companies such as Google, Microsoft Azure and Amazon are the leaders in this area, having developed different ML platforms. While AI and ML may appear to be alien terminologies to many, we have been experiencing it without us even being aware of it. Some of the areas that you might have come into close contact with this technology are in image tagging by Facebook as well as spam detection by email providers. For Facebook, for example, uploaded images are tagged automatically using face or image recognition algorithms while email providers such as Gmail use ML to recognize patterns or selected words then filter spam messages accordingly. Now let us look at some problems that arise from machine learning.

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