Machine Learning: The Ultimate Guide for Beginners and Starters (Artificial Intelligence, Algorithms, Data Science, Machine Learning For Beginners)
English | 2017 | ASIN: B073NLM5LK | 33 pages | AZW3/PDF/EPUB (conv) | 0.5 Mb
English | 2017 | ASIN: B073NLM5LK | 33 pages | AZW3/PDF/EPUB (conv) | 0.5 Mb
Use This Helpful Guide to Start Your Machine Learning Experience Now!
No doubt you have heard the term, ‘Machine Learning” and wondered what it was all about. You may have looked it up and thought that it sounded a little too complicated but the fact that you are here tells me that your interest was piqued enough to want to learn it.
Machine learning is a kind of artificial intelligence. It gives a computer the ability to learn something without human intervention, without us having to write an explicit computer program to tell the computer exactly what to do. The focus of machine learning is on developing programs that are dynamic, that change as and when new data is made available.
If you have heard of or have any experience of data mining then you will find that the machine learning process is similar. Both look for patterns in data but, where data mining pulls data for a human to read, machine learning takes the data and looks for patterns, learning how to adjust the actions of the program accordingly.
You will hear of two types of machine learning algorithm – supervised and unsupervised. The former applies previous learning to new data while the latter can draw an inference from a dataset. An example would be Facebook. The news feed makes use of machine learning to make sure that your news feed is personal to you. Let’s say that you read or react to a post from a friend; Facebook will begin to show you more posts from that friend earlier in your feed instead of you having to scroll through to look for them. This is done through predictive analytics and statistical analytics, identifying patterns in your data and using those patterns to fill up your news feed.
I have split the book into two sections – the first gives you a bit of background in Machine Learning and what to expect, while the second part of the book is a practical example of a Machine Learning project that you can work through, right from installing Python to executing the project. This is only a basic project and I haven't gone too deep as I just want to give you an idea of what it is all about.
I won’t promise that machine learning is going to be easy and you do need to have a basic understanding of computer program, especially Python. What I will promise is to make this beginner’s guide as simple to follow as possible so that, by the end of it, you will feel ready to move on to something a little deeper.