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Arthur Samuel coined the term machine learning in the year 1959. He was a pioneer in Artificial Intelligence and computer gaming and defined machine learning as "Field of study that gives computer the capability to learn without being explicitly programmed". Here, the emphasis is on leveraging data and algorithms to stimulate human learning and gradually increase accuracy. It is also a use of AI that makes it possible for systems to gain knowledge and get better over time without having explicit programming. The development of computer programs that can access data and utilize it to learn for themselves is the main objective. Machine learning is employed in different applications, including automated translation, self driving cars, picture recognition and voice search.
How Does Machine Learning Work?
ML is a form of artificial intelligence that teaches computers to think in a similar way to how humans do i.e, learning and improving upon past experiences. It works by exploring data and identifying patterns and involves minimal human intervention. The main goal of ML is to make it possible for computers to learn on their own, without aid for humans, and to adapt their behavior accordingly.
Why Is Machine Learning Important?
Machine Learning today has all the attention it needs. It can automate many tasks, especially the ones that only humans can perform with their innate intelligence. Replicating this intelligence to machines can be achieved only with the help of machine learning.
Businesses can automate routine tasks. It also helps in automating and quickly create models for data analysis. Various industries depend on vast quantities of data to optimize their operations and make intelligent decisions. It helps in creating models that can process and analyze large amounts of complex data to deliver accurate results. These models are precise and scalable and function with less turnaround time. By building such precise Machine Learning models, businesses can leverage profitable opportunities and avoid unknown risks.
Image recognition, text generation, and many other use-cases are finding applications in the real world. This is increasing the scope for machine learning experts to shine as a sought after professionals.
Application Of Machine learning
HealthCare
ML is used to analyse massive healthcare data sets to accelerate the discovery of treatments and cures, improve patient outcomes, and routine automatic processes to prevent human error. For example, IBM Waston uses data mining to provide physicians data they can use to personalize patient treatment.
Image Recognition.
Image recognition is one of the most common applications of machine learning. It is used to identify objects, persons, places, digital images, etc.
Speech Recognition.
While using Google, we get an option of "Search by voice," it comes under speech recognition, and it's a popular application of machine learning.
Speech recognition is a process of converting voice instructions into text, and it is also known as "Speech to text", or "Computer speech recognition." At present, machine learning algorithms are widely used by various applications of speech recognition. Google assistant, Siri, Cortana, and Alexa are using speech recognition technology to follow the voice instructions.
Manufacturing
As an Industry, Manufacturing is the backbone of any healthy economy. From optimized resource planning to cut short the time to market, Machine learning is helping the transformation of the manufacturing sector.
Marketing In a world of 25 billion-plus connected devices, machine learning plays a vital role in personalized digital marketing. Ads click prediction, showing relevant Ads to customers, identifying target customers, churn analysis, etc., are important applications of machine learning in the marketing sector.
Banking And Finance In a digital economy, machine learning helps banks and other financial organizations to safeguard from frauds, money laundering, illegal financial detection, identifying valuable customers, etc. It also helps financial organizations with stock market predictions, demand forecasting, offering personalized banking solutions to the customers, etc.
Automobile An automobile is another sector where the impact of machine learning is huge. Almost every automobile manufacturer uses artificial intelligence to optimise fuel consumption, breakdown prediction, and even self-driving. Tesla, Nvidia, etc., are investing a lot over self-driving cars. Speech Recognition While using Google, we get an option of "Search by voice," it comes under speech recognition, and it's a popular application of machine learning.
Speech recognition is a process of converting voice instructions into text, and it is also known as "Speech to text", or "Computer speech recognition." At present, machine learning algorithms are widely used by various applications of speech recognition. Google assistant, Siri, Cortana, and Alexa are using speech recognition technology to follow the voice instructions.
- Traffic prediction: If we want to visit a new place, we take help of Google Maps, which shows us the correct path with the shortest route and predicts the traffic conditions.
It predicts the traffic conditions such as whether traffic is cleared, slow-moving, or heavily congested with the help of two ways:
Real Time location of the vehicle form Google Map app and sensors Average time has taken on past days at the same time. Everyone who is using Google Map is helping this app to make it better. It takes information from the user and sends back to its database to improve the performance.
- Product recommendations: Machine learning is widely used by various e-commerce and entertainment companies such as Amazon, Netflix, etc., for product recommendation to the user. Whenever we search for some product on Amazon, then we started getting an advertisement for the same product while internet surfing on the same browser and this is because of machine learning.
Google understands the user interest using various machine learning algorithms and suggests the product as per customer interest.
As similar, when we use Netflix, we find some recommendations for entertainment series, movies, etc., and this is also done with the help of machine learning.
Self-driving cars: One of the most exciting applications of machine learning is self-driving cars. Machine learning plays a significant role in self-driving cars. Tesla, the most popular car manufacturing company is working on self-driving car. It is using unsupervised learning method to train the car models to detect people and objects while driving.
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