With many new coders who are getting into the field of AI there is always a want to start coding as soon as possible. I was like that too, enthusiastic and eager to make something happen out of nothing. Eventually as I stared devolving a mature state of mind, but I still dove straight into deep learning and started to learn that. There was nothing wrong in it, but it contained a lot of formulars and structure which I understood, but I know that there were gaps that were being formed. Yes, one could go back and fill those gaps, but the foundation would still be weak. This is a similar feeling to when a solder is forced down to a battlefield without preparation.

From then on, I set a regiment where first, I would learn the concept theoretically (Yes, this includes some formulas) then I apply that knowledge though practical means. Let me mention that I have never blogged about anything. I am sure that this blog has a bunch of spelling mistake and really poor sentence structure. I am really sorry for that, but on the other hand, I am sure you will understand the content irrespective of me writing as Shakespeare or like a middle school boy.

Now that that is out of the way this is going to be a series of blogs that I want to write about AI and its fields. While my reason is somewhat selfish, I would get a deeper understanding by writing blogs, i still have to help people with the field people I love it. This particular blog is just going to an introduction/information about Machine Learning. I am sure you may think that you know everything but it worth a read.

What is Machine Learning?

Great scientists always ask questions. Some scientists must have said that I just used that sentence to show my literacy in English. Anyway, so ask questions. What is Machine Learning? When you go you IBM's website, they describe it as a branch of machine learning and computer science with focusses on the use of data and algorithms to imitate the way humans learn. It gradually corrects itself to incense accuracy. We as humans are trying to mimic the human brain.

Machine Learning is a popular growing field in data science where they are able to extrapolate data and analyze it to predict certain things. These data then can be used for decision making within applications and businesses.

Nowadays we hear a lot of buzz words such as deep learning machine leaning etc. Frankly some even use them interchangeably. Machine learning, deep learning and neural networks are all subfields of artificial intelligence. Deep learning is actually a sub field of machine leaning. Deep learning focus on how the algorithm learns. It extracts information and eliminates human interaction required by acquire knowledge by large data sets.

Machine Learning can be used in internet search engines, email filters to sort out spam, websites to make personalized recommendations, banking software to detect unusual transactions, and lots of apps on our phones such as voice recognition.

With all that said, now we can continue knowing the importance of machine learning. In the following days the first blog regarding classification will be added. Keep coding till then