Machine learning is the way in which we train computers to make them learn by themselves.
In other words – It is the process of making a computer conscious of its environment and gives it the ability to learn by itself by trial and error.
In the past decade, machine learning has given us self-driving cars like the well known Tesla, speech recognition like that of Google, a better and more effective web search, and a vastly improved understanding of the human genome. Even companies like Facebook is using machine learning to recognize spam. Machine learning is spread so vastly in today’s generation that you probably use it dozens of times a day without knowing much or evening nothing about it. Many researchers also think it is the best way to make progress towards human-level AI.
You maybe have seen the movie WALL-E ? or maybe I-Robots, they are examples of what machines are capable of now and in the future, to self-develop and advance in their thinking and carrying out tasks themselves by learning from human beings.
Machine learning works on the basis of algorithms. It is also considered the family of algorithms that can find different patterns in data, Building algorithms capable of doing this, using the binary “yes” and “no” logic of computers. We can also say Machines have the capability to learn from data. Once the machine finds a pattern, the data can be dumped and just use the, much smaller, pattern to do something useful. This is basically what learning is.
When you learn how to drive, you don’t memorize every second of driving practice and run over it in your head as you’re driving. That information/experience is used build a model in your head of how to drive. The model informs your actions, telling you how to react to different circumstances. The model is the pattern you take away from the experience of driving. Human Beings learn from what information is exposed to them, the same way machines are made to learn by exposing them to different situations.
What can be done with machine learning?
The application of machine learning to society and industry in today’s generation is leading to advancements in many fields of human endeavor.
If we take an example, such as, in medicine, machine learning is being applied to genomic data to help doctors understand, and predict, how cancer spreads, meaning more effective and better treatments can be developed for human beings who battle cancer and many other diseases.
Data from deep space is being collected here on Earth through huge radio telescopes and after being analyzed with machine learning helps us to unlock the secrets of black holes.
In the war against terrorism and extremism, machine learning is used to predict the behavior of those wanting to harm the innocent.
In retail, machine learning helps by matching shoppers with products they want to buy online and allows shop assistants to personalize the service they offer their customers.
In our day-to-day lives, machine learning now powers Google’s search and image algorithms, to provide us with more revised information we need in our lives, whenever and wherever we need it.
The process of allowing computers to understand and communicate with us in human language, thanks to machine learning, is known as natural language processing (NLP) and this has led to breakthroughs in translation technology and the voice controlled devices we increasingly use every day, including Amazon’s Echo.
Without a doubt, machine learning is proving itself to be a technology with far-reaching transformative powers. The science fiction dream of robots capable of working alongside us and augmenting our own inventiveness and imagination with their flawless logic and superhuman speed is no longer a dream – it is becoming a reality in many fields. Machine learning is the key which has unlocked it, and its potential future applications are almost unlimited.
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