How machine learning and deep learning can improve our daily lives in future

Undeniably, artificial intelligence has become one of the most talked-about areas of the IT domain.
The terms “artificial intelligence,” “machine learning” and “deep learning” are often thrown about interchangeably.AI is just a container. You don’t learn AI. I’ll not confuse with terms.
Let’s see the difference between Deep Learning And Machine Learning-
Machine learning, which is a type of artificial intelligence (AI), was born in the 1950s. Arthur Samuel wrote the first computer learning program in 1959, in which an IBM computer got better at the game of checkers the longer it played. Where as in deep learning You may already have experienced the results of an in-depth deep learning program without even realizing it! If you’ve ever watched Netflix, you’ve probably seen its recommendations for what to watch. And some streaming-music services choose songs based on what you’ve listened to in the past.While machine learning uses simpler concepts like predictive models, deep learning uses artificial neural networks designed to imitate the way humans think and learn.
THE FUTURE
• Machine learning
Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.Machine learning is being used in a wide range of fields: art, science, finance, healthcare—you name it. And there are different ways of getting machines to learn.In other words, they continuously improve their performance on a task—for example, playing a game—without additional help from a human.It’s helpful to know R or Python if you want to delve more deeply into machine learning with R and machine learning with Python.Supervised machine learning algorithms ,unsupervised machine learning algorithms ,Semi-supervised machine learning algorithms ,Reinforcement machine learning algorithms are some of the machine learning methods.Basic machine learning applications include predictive programs (such as for forecasting prices in the stock market or where and when the next hurricane will hit), email spam identifiers, and programs that design evidence-based treatment plans for medical patients.
• Deep Learning
Deep learning allows machines to solve complex problems even when using a data set that is very diverse, unstructured and inter-connected.In addition to the examples mentioned above of Netflix, music-streaming services and facial recognition, one highly publicized application of deep learning is self-driving cars—the programs use many layers of neural networks to do things like determine objects to avoid, recognize traffic lights and know when to speed up or slow down. The healthcare industry also will likely change, as deep learning helps doctors do things like to predict or detect cancer earlier, which can save lives.
As you may have figured out by now, it’s an exciting (and profitable!) time to be a machine learning engineer. So there has never been a better time to begin studying to be in this field or deepen your knowledge base.
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