# ML World: Learn Machine Learning! Part 2

This tutorial answers all the following questions:

1. What are the different types of Regression Analysis?
2. What is Simple Linear Regression?
3. How does Simple Linear Regression find the best fit line?
4. What are the assumptions of Simple Linear Regression?
5. How to Implement a Simple Linear Regression model?

# ML World: Learn Machine Learning! Part 1

This tutorial answers all the following questions:

1. Why Machine Learning?
2. What is Labeled data and Unlabeled data?
3. What are the types of Machine Learning?

Congratulations on completing the Data Preprocessing Series. Welcome to ML world!

You have sorted out all the problems with dirty data, and…

# Six steps to hone your Data: Data Preprocessing, Part 6

Finally, this part marks the end of our Data Preprocessing journey. We were introduced to what Data Preprocessing is, why it is important, and how the first five steps of Data Preprocessing are carried out, so far in our series.

If you have not checked out the previous tutorials of…

# Six steps to hone your Data: Data Preprocessing, Part 5

Throughout this series, we have come across various faults that could harm the accuracy of our data or may result in our ML model being trained inappropriately.

What exactly is this ‘Training a model’?How is the accuracy of our model calculated?

So far, we imported libraries, imported our dataset, cleaned…

# Six steps to hone your Data: Data Preprocessing, Part 4

This tutorial answers all the following questions:

1. What happens when categorical values are passed to ML models?
2. How to encode categorical values?

We have almost covered 50% of our data preprocessing journey.

It is quite conspicuous now, that if we need our ML model to…

# Six steps to hone your Data: Data Preprocessing, Part 3

This tutorial answers all the following questions:

1. When does the problem of missing values arise?
2. Why is it essential to handle missing values?
3. How are missing numeric values handled?
4. How are categorical missing values handled?

So far, we have clear intuition on how to import…

# Six steps to hone your Data: Data Preprocessing, Part 2

Assuming you have a clear intuition about what data processing is, we will now venture towards the next step.

If you have not checked out the first step of Data preprocessing yet, I would suggest you read our previous article.

# Six steps to hone your Data: Data Preprocessing, Part 1

## Who is the targeted audience?

This tutorial is for anyone wishing to start their Machine Learning journey or want to brush up some concepts. Data Preprocessing is an essential part of your ML journey, as you move ahead, you will realize the critical role data preprocessing plays in building, training, and testing your models accurately.

# The Three Musketeers of ML: Introduction to NumPy, Pandas and Sklearn .

## Who are the targeted audience?

This tutorial has been prepared for those who want to learn about the basics of NumPy, Pandas and Sklearn. It is specifically useful for algorithm developers and anyone who is curious about Machine Learning and wants to have in depth knowledge about ML or just needs to brush up a…

# Beginners Guide to Machine Learning: Data Pre-processing using Python.

The journey of learning machine learning is super long but yet very exciting!

If you are a beginner, this blog is just what you need to get your head start! Data processing is the first tool you learn as a machine learning practitioner. Let’s get started! 