Some data that we obtain from the internet are gained as a raw, means that there are no modifications done to the data except placing it in the right column or row. Even if that’s a good thing, sometimes you have to treat and change the template of the data to be as friendly to reach our objective as possible.
Time series involves data collected sequentially in time. In Feed Forward Neural Network we describe that all inputs are not dependent on each other or are usually familiar as IID (Independent Identical Distributed), so it is not appropriate to use sequential data processing.
A Recurrent Neural Network (RNN) deals with sequence problems because their connections form a directed cycle. In other words, they can retain state from one iteration to the next by using their own output as input for the…
Evaluating your machine learning algorithms is important part in your project. Choice of metrics influences how the performance of machine learning algorithms is measured and compared. Metrics evaluation used to measure the performance of our algorithms. For Regression models, we usually use R-squared and MSE, but for Classification models we can use precision, recall and accuracy. Evaluating a classifier is often much more difficult than evaluating a regression algorithm. Usually, after we’ve…
We’ll set-up caching for this notebook given how computationally expensive some of the code we will write can get.
When you start coding in R you probably get a lot of errors, and trying to decipher an error can be a time-consuming task. You might need to Google or maybe you asked for help to your friends/mentor and they find out you’ve forgot a closing bracket!.
Time Series Analysis describes a set of research problems where our observations are collected at regular time intervals and where we can assume correlations among successive observations. The principal idea is to learn from these past observations any inherent structures or patterns within the data, with the objective of generating future values for the series. Time series may contain multiple seasonal cycles of different lengths. A fundamental goal for multiple seasonal (MS) processes is to…
Social media has become a very popular spot for data mining these last years. But when we talk about social data, we actually also talk about unstructured data, and in order to derive any meaningful insight from it, we have to know how to work with it in its unstructured form (or in this case, unstructured text information).
Cause has been people’s curiosity for a long time, you can see that people often ask “Why” to things happening around them.
But do we actually know how to explain “cause”?
Do we jump to conclusion of causal relationship often too quickly?
Can association between factors that we call mathematically “correlation” tell us possible causal relationship? No. Correlation shows whether two variable go up or down together. But just because two variables go up…
Support Vector Machine is a Supervised Machine Learning Algorithm which can be used both classification and regression. In this algorithm, each data item is plotted as point in n-dimensional space with the value of each feature being the value of a particular coordinate. Then, the algorithm perform classification by finding the hyper-plane that differentiate the two classes very well.
