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How to Learn Mathematics for Machine Learning?
- First option has to be learning through books. There are many books available which are excellent to start with.
- Now a days there are many courses available and these are the best way to kick start your machine learning journey. Both students and professionals will have an edge over all other applicants if they leverage these degree or a certification on the same. I would personally recommend Intro to Machine Learning - GL4L because the tutorial is absolutely free and very easy to understand for a beginner. Therefore it is advisable to take advantage of this course and understand the basics of machine learning as it will give you a very good idea about the whole machine learning concept. Things are taught step by step, it is all hands-on and not theoretical. It is easy to get lost and waste time learning many different aspects. I like this course because it covers only what is needed and no more and it is well explained.
- Deep learning, a subset of machine learning, utilizes a hierarchical level of artificial neural networks to carry out the process of machine learning. The artificial neural networks are built like the human brain, with neuron nodes connected together like a web. While traditional programs build analysis with data in a linear way, the hierarchical function of deep learning systems enables machines to process data with a nonlinear approach. A traditional approach to detecting fraud or money laundering might rely on the amount of transaction that ensues, while a deep learning non-linear technique would include time, geographic location, IP address, type of retailer and any other feature that is likely to point to a fraudulent activity.
- Ensemble Modelling is a powerful way to improve the performance of your model. It usually pays off to apply ensemble learning over and above various models you might be building. Learning this is where an expert can be differentiated from an average professional.
- Machine Learning with Big Data As you know that the size of data is increasing at an exponential rate but raw data is not useful till you start getting insights from it. Machine learning is nothing but learning from data, generate insight or identifying pattern in the available data set. There are various application of machine learning.