How can we relate standard deviation and variance?

Standard deviation refers to the spread of your data from the mean. Variance is the average degree to which each point differs from the mean i.e. the average of all data points. We can relate Standard deviation and Variance because it is the square root of Variance. Standard deviation and variance are both measures of … Read more

We look at machine learning software almost all the time. How do we apply Machine Learning to Hardware?

We have to build ML algorithms in System Verilog which is a Hardware development Language and then program it onto an FPGA to apply Machine Learning to hardware. Applying machine learning to hardware involves leveraging techniques from the field of hardware-aware machine learning. Here are several ways in which machine learning can be applied to … Read more

How are covariance and correlation different from one another?

Covariance measures how two variables are related to each other and how one would vary with respect to changes in the other variable. If the value is positive it means there is a direct relationship between the variables and one would increase or decrease with an increase or decrease in the base variable respectively, given … Read more

How do you select important variables while working on a data set?

There are various means to select important variables from a data set that include the following: Identify and discard correlated variables before finalizing on important variables The variables could be selected based on ā€˜pā€™ values from Linear Regression Forward, Backward, and Stepwise selection Lasso Regression Random Forest and plot variable chart Top features can be … Read more

What is the main key difference between supervised and unsupervised machine learning?

Supervised learning technique needs labeled data to train the model. For example, to solve a classification problem (a supervised learning task), you need to have label data to train the model and to classify the data into your labeled groups. Unsupervised learning does not need any labelled dataset. This is the main key difference between … Read more