Updated: Apr 7, 2020
Introduction to ML
Machine Learning today is undoubtedly one of the most influenced and ever advancing technology in today's world. There is no doubt that it continues to make the headline in the coming future . Here, this article is designed in a manner which tells us about the complete in and out of Machine Learning in a detailed way.
Evolution of Machine Learning?
With the advancement of new technologies every now and then, the machine learning today is not the machine learning in the past. It came into existence from the pattern recognition and also from the theory which states that machines can learn and perform its functions on its own without actually being programmed by humans. The researchers and scientists wanted to check if the machines can perform its function by means of data analysis.
Machine Learning is an important aspect of modern day research and development irrespective of the fields, or, I would rather say, for the betterment of the fields that ML is used in. It uses algorithms and neural network models to assist computer systems in progressively improving their performance.
Algorithms that Machine Learning uses will automatically build a mathematical model using sample data – also known as “training data” which enables to make decisions without being specifically programmed to make those decisions.
Oh yeah, Sorry I KEPT YOU WAITING For long, but What is this Machine Learning?
Machine Learning is one of the applications of AI that gives the system the ability to automatically learn and improve its performance from experience. It is a type of understanding in which a machine can learn by its own without being clearly programmed by the inputs of human. Machine learning’s major focus is on the development of computer programs that can access data and use it for the betterment of themselves.
Machine learning is also a type of data analysis that automates analytical model building. It is that branch of artificial intelligence which is based on the idea that systems can learn from data, identify patterns and also make decisions with a very minimal human intervention.
The Journey of Automation
In the Environment of Machine learning, or setup various algorithms and services are managed between the actual source of the data and the learning platform which can be on the cloud. ML today in all cases does its work on centralized infrastructure, though there are some success stories where it also runs exceptionally well on a distributed infrastructure. These methods may/may not be at the most efficient but for now, they work well.
Machine Learning is advanced and has evolved in its own way. Machine learning has evolved from being a subset of Artificial Intelligence to its own domain, although not completely. Now, Machine Learning is reached to an untouchable heights, at least in terms of messaging. The journey has now come to an extend wherein normal machines are being transformed to Robots which act like humans. It is difficult to measure the amount of automation and advancements that the machine learning has gained now a days. In recent times, the term machine learning and the usage of the same is becoming more in business and various fields.
“A focal point where business, data, experience meets emerging technologies and decides to work together”.
In the terms of AILabPage, the term machine learning is as simple as it is in the mentioned above.
Important Programming languages
At the time of choosing languages to get specialized in the field of machine learning, you might want to consider the various factors including the skills mentioned in the your current job advertisement i.e., your resume or any other source that you have applied to.
In the latest survey conducted by various researchers, it states that Python is one programming language which has gained a lot of popularity in the field of machine learning. Python is followed by Java, then R, then C++.
Python is one such language which has the ability to be used as a scripting language. The reason for Python’s popularity may be due to the increased development of deep learning frameworks available for this language off late, including TensorFlow, PyTorch, and Keras. Python proves to be powerful and straightforward both for pre-processing data and working with data directly.
R is a kind of software that acts as an open source programming language used primarily for statistical computing. It is gaining a lot of popularity in the non-technical field and is used primarily for statistical computing. R is not typically used in industry production environments, but has risen in industrial applications due to increased interest in data science.
C++ is a language of choice for both artificial intelligence and machine learning, in game or robot applications. Embedded computing hardware developers and electronics engineers are more likely to favor C++ or C in machine learning applications due to their proficiency and level of control in the language.
In the coming future, there is no doubt that machine learning is going to be everywhere and people should not really wonder looking at the advancements Machine Learning is going to make in the future. Because machine learning is a field that is continuously being innovated, it is important to keep in mind that algorithms, methods, and approaches will continue to change.
If you are looking to start a course with AI & ML, we at Infimind Institute, help achieve the dream and goal of by conducting an academic course of Artificial Intelligence and Machine Learning.