Introduction to different Machine Learning tools
It is now common knowledge in the world of technology that Machine Learning, an offshoot or subset of Artificial Intelligence, is a game changer. We have seen many such gamechangers in the past; so, why should this one make us sit up and take notice? Simple: it is a game changer for all the industries in which it makes an impact. Machine Learning is making an impact of unseen magnitude in a swathe of activities and industries by facilitating work to an extent that was not imagined earlier. So, which are the tools in Machine Learning? Before getting down to getting an understanding of these tools, let us first try to figure out what tools mean in this context. As with all other technologies, tools in Machine Learning too mean the same: something that aids or smooths the functioning of this technology. Tools are needed to help the programming language, or for that matter, any aspect of a technology, to enable its functions. We can think of tools as being similar to the clutch, gear and steering wheels in an automobile. In the context of Machine Learning, tools are what move the program and help them carry out its roles and objectives. One standout feature of Machine Learning tools is that most of them are Open Source, meaning that anyone can contribute to them and enrich them. The Open Source method is considered a milestone in democratizing technologies, and it must be said, it has largely succeeded at this.
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