Starting Machine Learning with an End-to-End Project

When you are learning about Machine Learning, it is best to experiment with real-world data alongside learning concepts. It is even more beneficial to start Machine Learning with a project including end-to-end model building, rather than going for conceptual knowledge first.

Benefits of Project-Based Learning

You get to know about real-world projects which in a way prepares you for real-time jobs.
Encourages critical thinking and problem-solving skills in learners.
Gives an idea of the end-to-end process of building a project.
Gives an idea of tools and technologies used in the industry.
Learners get an in-depth understanding of the concepts which directly boosts their self-confidence.
It is a more fun way to learn things rather than traditional methods of learning.

What is an End-to-End project?

End-to-end refers to a full process from start to finish. In an ML end-to-end project, you have to perform every task from first to last by yourself. That includes getting the data, processing it, preparing data for the model, building the model, and at last finalizing it.

Ideology to start with End to End project

It is much more beneficial to start learning Machine Learning with an end-to-end project rather than diving down deep into the vast ocean of Machine Learning concepts. But, what will be the benefit of practicing concepts without even understanding them properly? How to implement concepts when we don’t understand them properly?

There are not one but several benefits of starting your ML journey with a project. Some of them are:

You have an idea of building an ML model from the beginning

When you do an end-to-end project, you get to know about the workflow of designing an ML model. Therefore, you already know the end goal while learning ML concepts. This makes the journey much easier as you already have a clear vision of the end goal.

Understanding use cases of concepts beforehand

Many learners get confused in the beginning while learning ML concepts. The most common doubts are:

What is the use of this concept?
Is learning this concept really important?
At what stage/step will we have to use this concept in the real world?

This not only wastes the time of the learner but also brings down their self-confidence and excitement to learn. But when you have already done a project at starting, you know the answers to these questions beforehand.

Helps in deciding the learning path

Beginners are always confused with their learning path. For example, how to start? Which topics to learn first? What should be the learning path for Machine Learning? In which sequence should I learn the concepts?

In an end-to-end project, you learn how to build a Machine Learning model from the first step to the last, i.e., from understanding the problem(whether it’s supervised, unsupervised, etc) to monitoring the system. This helps learners to decide in which sequence they should learn the concepts as they already know in what sequence the model building is carried out. Therefore, learners can choose their learning path wisely.

Up to what level to learn a particular concept

As they say, knowledge is a never-ending journey. But, gaining knowledge demands time which is much rare in today’s world. Also, machine learning is a vast field. Therefore, it is much important to know how much time you should give to a particular topic.

When you have already done an end-to-end project, you already have a blurry vision of how the concept is used while building a model and what factors of that topic can affect the project. That helps a lot in deciding how much to emphasize on a particular topic.

Get a better understanding of ML concepts

Having a prior idea of the concept makes understanding it much easier. And, while building the project we grasp a little idea of the concept. So when we study the topic, it doesn’t seem like a complete stranger but a good old friend.

Q. How to implement concepts when we don’t understand them properly?

You don’t need a good understanding of the concept to implement them in code. Thanks to the various libraries and tools which make our work so much easier. Think of a task and there is already a function to perform it. So, all you need is just a little introduction to the topic and you are ready to implement it in code.

But, where to find such a project which includes the ‘little introduction‘ to the topic and will provide us with a sequence of steps needed to be followed to build an end-to-end ML project. As a beginner, it would be difficult to do a project without guidance.

Where to find such a project?

Don’t worry! We got your back there as we have prepared a beginner-friendly end-to-end project for Machine Learning. The only prerequisite of the project is to know Python. Other than it, everything is covered in the project itself.

Also, our end-to-end project is free of cost.

For learning Python, you can refer to our Python playlist.

Check out our End to End ML project at End to End ML Project- Beginner friendly.

Why choose this project?

This project is prepared while keeping beginners in mind. It will walk you through all the steps included in a Machine Learning Pipeline in detail.
It is free of cost.
You will learn the answers to the three most important questions, i.e., Why, When, and How to do a particular thing.
The concepts used in performing a step are explained there and then in a simple way for beginners.
This project follows a no-spoon-feeding approach. So, a particular concept is explained and then you have to figure it out on your own whether the problem given to you can be solved by that concept or not.
Hints and Answers are provided at every step to make it more beginner-friendly.
Our assessment engine will judge your solution and provide you with the result there and then. It will also tell you where have you made the mistake so you can correct it.
You will gain knowledge of several libraries commonly used in the ML world and will learn how to use them.
You don’t need to install any software in your system and can practice these concepts in our cloud lab itself.
Why don’t you figure it out on your own? Check out our End to End project.

Note: This project is for learners who like to use their brains because learners will have to complete every step on their own. We will just provide you with the instructions to perform a particular step. All the work, you will have to do on your own. But don't worry, in case you get stuck, hints and answers are provided at every step.