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I am new to the data science community and wanted to understand the required steps that need to be taken into account while handling a dataset that does not have a target variable. I can do machine learning on top of a labeled dataset having a target variable but not sure what would be the best way to start with a dataset where is there is no target variable. I am aware that this is a classification problem on which I am working on.

Could you please help me with the right step by step guide that I should follow in order to achieve an efficient clustering at the end?

Do I need to do the following in order to achieve that:

1. Data Cleansing
2. EDA
3. Encoding and scaling
4. Model build
5. Validation

Or are there any more steps that I need to take care of while dealing with an unsupervised class of data. I am doing this in python

I want to understand the required steps that need to be taken into account while handling a dataset that does not have a target variable. I can do machine learning on top of a labeled dataset having a target variable, but not sure what would be the best way to start with a dataset where is there is no target variable.

I need a step by step guide to achieve an efficient clustering at the end.

Do I need to do the following in order to achieve that?:

1. Data Cleansing
2. EDA
3. Encoding and scaling
4. Model build
5. Validation

Or are there any more steps that I need to take care of while dealing with an unsupervised class of data. I am doing this in python

I am new to the data science community and wanted to understand that the required steps that need to be taken into account when handling a dataset that does not have a target variable. I can do machine learning on top of a labeled dataset having a target variable but not sure what would be the best way to start with a dataset where is there is no target variable. I am aware that this is a classification problem on which I am working on.

Could you please help me with the right step by step guide that I should follow in order to achieve an efficient clustering at the end?

Do I need to do the following in order to achieve that:

1. Data Cleansing
2. EDA
3. Encoding and scaling
4. Model build
5. Validation

Or are there any more steps that I need to take care of while dealing with an unsupervised class of data. I am doing this in python

I am new to the data science community and wanted to understand the required steps that need to be taken into account while handling a dataset that does not have a target variable. I can do machine learning on top of a labeled dataset having a target variable but not sure what would be the best way to start with a dataset where is there is no target variable. I am aware that this is a classification problem on which I am working on.

Could you please help me with the right step by step guide that I should follow in order to achieve an efficient clustering at the end?

Do I need to do the following in order to achieve that:

1. Data Cleansing
2. EDA
3. Encoding and scaling
4. Model build
5. Validation

Or are there any more steps that I need to take care of while dealing with an unsupervised class of data. I am doing this in python

I am new to data science community and wanted to understand that the required steps that needs to be taken into account when handing a dataset that does not have a target variable. I can do machine learning on top a labelled dataset having target variable but not sure what would be the best way to start with a dataset where is there is no target variable. I am aware that this is a classification problem on which I am working on.

Could you please help me the right step by step guide that I should follow in order to achieve an efficient clustering at the end?

Do I need to do the following in order to achieve that:

1. Data Cleansing
2. EDA
3. Encoding and scaling
4. Model build
5. Validation

Or are there any more steps that I need to take care off while dealing with an unsupervised class of data. I am doing this in python

I am new to the data science community and wanted to understand that the required steps that need to be taken into account when handling a dataset that does not have a target variable. I can do machine learning on top of a labeled dataset having a target variable but not sure what would be the best way to start with a dataset where is there is no target variable. I am aware that this is a classification problem on which I am working on.

Could you please help me with the right step by step guide that I should follow in order to achieve an efficient clustering at the end?

Do I need to do the following in order to achieve that:

1. Data Cleansing
2. EDA
3. Encoding and scaling
4. Model build
5. Validation

Or are there any more steps that I need to take care of while dealing with an unsupervised class of data. I am doing this in python