**Bias:**Bias can be defined as a situation where an error has occurred due to use of assumptions in the learning algorithm.

**Variance: **Variance is an error caused because of the complexity of the algorithm that is been used to analyze the data.

**The following are few methods can be used to select important variables:**

- Use of Lasso Regression method.
- Using Random Forest, plot variable imprtance chart.
- Using Linear regression.

Deep learning is a process where it is considered to be a subset of machine learning process.

Yes, it is possible by using ANCOVA technique. It stands for Analysis of Covariance.

It is used to calculate the association between continuous and categorical variables.

They are generally used for database indexing.

A hash table is nothing but a data structure that produces an associative array.

An individual can easily find missing or corrupted data in a data set either by dropping the rows or columns. On contrary, they can decide to replace the data with another value.

In Pandas they are two ways to identify the missing data, these two methods are very useful.

isnull() and dropna().

Data mining is about working on unstructured data and then extract it to a level where the interesting and unknown patterns are identified.

Machine learning is a process or a study whether it closely relates to design, development of the algorithms that provide an ability to the machines to capacity to learn.

The relation is

True Positive Rate = Recall.

- Model building
- Model testing
- Applying the model

- Nearest Neighbour
- Neural Networks
- Decision Trees etc
- Support vector machines