In this video, What is Machine Learning? we will briefly look at the definition of machine learning. We will have Machine Learning Explained with the help of examples and look at how Machine Learning will change the future in this series #Shorts by Simplilearn.

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What is Machine Learning?
A good start at a Machine Learning definition is that it is a core sub-area of Artificial Intelligence (AI). ML applications learn from experience (well data) like humans without direct programming. When exposed to new data, these applications learn, grow, change, and develop by themselves. In other words, with Machine Learning, computers find insightful information without being told where to look. Instead, they do this by leveraging algorithms that learn from data in an iterative process. While the concept of Machine Learning(ML) has been around for a long time (think of the WWII Enigma Machine), the ability to automate the application of complex mathematical calculations to Big Data has been gaining momentum over the last several years. At a high level, Machine Learning is the ability to adapt to new data independently and through iterations. Basically, applications learn from previous computations and transactions and use “pattern recognition” to produce reliable and informed results.

How does Machine Learning work?
Machine Learning is, undoubtedly, one of the most exciting subsets of Artificial Intelligence. It completes the task of learning from data with specific inputs to the machine. It’s important to understand what makes Machine Learning work and, thus, how it can be used in the future. The Machine Learning process starts with inputting training data into the selected algorithm. Training data being known or unknown data to develop the final Machine Learning algorithm. The type of training data input does impact the algorithm, and that concept will be covered further momentarily. To test whether this algorithm works correctly, new input data is fed into the Machine Learning algorithm. The prediction and results are then checked. If the prediction is not as expected, the algorithm is re-trained multiple numbers of times until the desired output is found. This enables the Machine Learning algorithm to continually learn on its own and produce the most optimal answer that will gradually increase in accuracy over time.

About Simplilearn Machine Learning Certification Course:
Explore this Machine Learning certification course to understand cutting-edge concepts in machine learning, an exciting branch of Artificial Intelligence. This Machine Learning online training will provide you with the skills needed to become a successful Machine Learning Engineer today.

Machine Learning Course Overview:
This Machine Learning course offers an in-depth overview of Machine Learning topics including working with real-time data, developing algorithms using supervised & unsupervised learning, regression, classification, and time series modelling. Learn how to use Python in this Machine Learning certification training to draw predictions from data.

Key Features of this Machine Learning Course:
✅100% Money-Back Guarantee
✅Gain expertise with 25+ hands-on exercises
✅4 real-life industry projects with integrated labs
✅Dedicated mentoring sessions from industry experts

Eligibility for this Machine Learning Course:
The Machine Learning certification online course is well-suited for participants at the intermediate level including, analytics managers, business analysts, information architects, developers looking to become data scientists, and graduates seeking a career in Data Science and Machine Learning.

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