What are the Prerequisites to Learn Machine Learning?

This blog has a list of prerequisites to learn machine learning from scratch.

What are the Prerequisites to Learn Machine Learning?
 |  BY Manika

In this blog, we have mentioned all the topics that are considered as prerequisites for learning machine learning. We have covered all the subjects and the best resources that will help you learn them thoroughly.

Upskilling in the era of the Internet has become hassle-free.The Internet has given a platform to experts who can now share their knowledge with a large number of people and help those people in acquiring new skills irrespective of their previous knowledge about the subject. Machine learning is no exception to that.


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One can easily learn Machine learning without any hassle if they are made aware of the right resources. And no, you don’t need to worry about your non-mathematical educational background because learners of machine learning are not restricted to a particular field and rather span different domains. You can be an undergraduate student who is simply curious about machine learning or a working professional like a software developer who wants to diversify their skillset. Machine learning(ML) is for anyone who has the zeal and dedication for understanding it. So, if you are considering pursuing the path of learning ML but you think your educational background is not enough, you need to reconsider that because most beginners learn ML from scratch.

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Before a chef starts preparing any dish, the first thing they do is ensure that they have all the ingredients in the right amount on their table. Similarly, for all the individuals who are considering machine learning as a career option, it is important to know what are the prerequisites for machine learning. So, without any further ado, let us start with our list of prerequisites for learning machine learning.

Prerequisites to Learn Machine Learning

Before diving into the prerequisites list, we suggest that you motivate yourself a bit by reading a short section on what makes machine learning worthy of your time and energy. You can skip this section if you already fancy machine learning.

Why should you learn Machine learning?

Machine Learning, Machine Learning, Machine Learning! This domain of artificial intelligence has created a buzz in the tech world that seems to rise exponentially. The buzz is so intense that so many institutions are joining hands to launch new courses because of the rising demand to explore machine learning among young students. Not only that, but many professionals are also investing their time in understanding machine learning methods to become more efficient at their jobs.

If you think machine learning methods may not be of use to you, we reckon you reconsider that because, in May 2021, Gartner has revealed that about 70% of organisations will shift their focus from big to small and wide data by 2025. This statistic suggests that the popularity of machine learning (ML) among different organisations is definitely going to increase in the future.

Machine Learning is receiving so much traction because it reveals insightful facts from a given dataset that would not have been gained access to by using other tools. It simplifies complex problems by making probabilistic predictions for specific parameters in the dataset. Another reason behind the traction is the exciting range of application systems that can be created using ML. These include Handwriting Recognition System, Credit Card Fraud Detection System, Sales Forecasting Project, Stocks Price Prediction, etc. Let us now discuss one such fantastic application that has recently gone viral in India.

In India, the festival of lights, Diwali, is around the corner and Indians like to celebrate it by exchanging sweets and gifts with their near and dear ones. This year, to help small businesses grow, Cadbury India has come up with an exciting advertising campaign. The campaign uses Machine Learning and Artificial Intelligence methods to create customised advertising videos for the small shops where the world-famous celebrity Shah Rukh Khan will motivate the audience to buy from them.

You can also create such excellent Machine Learning-based applications soon if you are determined enough to learn about them. Along with strong determination, you need to work on a few prerequisites for machine learning before jumping into this exciting domain. 

List of Prerequisites for Machine Learning

In this section, you will find a list of prerequisites for learning machine learning from scratch.

The prerequisites have been split into the following categories for enhancing your browsing experience.

  • Basic Mathematical Prerequisites for machine learning

  • Linear Algebra Prerequisites for Machine Learning

  • Is Coding Required for Machine Learning?

  • Laptop Requirements for Machine Learning

If you are a newbie in ML and want to know the best resources for learning the prerequisites, continue reading as we explore the above list options in detail.

prerequisites to learn machine learning

Basic Mathematical Prerequisites for Machine Learning 

The basic math prerequisites for machine learning are usually covered in high school. One need not spend too much time practising maths problems as most complex problems can be solved using the built-in functions of a programming language. Those functions have been optimised already, so you don’t need to go in depth of the algorithms. However, if you are curious about how they are optimised, we recommend you go through the book mentioned below.

Book Recommendation: Mathematics for Machine Learning by Marc Peter Deisenroth,

A. Aldo Faisal, Cheng Soon Ong

Get Closer To Your Dream of Becoming a Data Scientist with 70+ Solved End-to-End ML Projects

About the Book: The book has been divided into two parts, where part 1 contains all the mathematics necessary for learning ML. It covers linear algebra, analytics geometry, matrix decompositions, probability and statistics, vector calculus, and continuous optimization in sufficient depth to help the reader quickly grasp such concepts. The book is available for free for personal use, and you may download it from the above link.

Recommended Reading: The Ultimate Guide to Statistics for Machine Learning Beginners

Linear Algebra Prerequisites for Machine Learning

While linear algebra is explained in the book we mentioned in the previous section, we suggest you study this topic in greater depth as machine learning algorithms are optimised by using matrix notation. Again, this is only necessary if you are interested in deeply understanding the mathematical complexities behind the optimisation of algorithms. Many people are more inclined towards learning by doing methodology than reading a book. For them, we recommend working on specific machine learning projects that will assist them in learning the implementation of linear algebra concepts in the real world.

Book Recommendation: Linear Algebra by Jim Hefferon

About the Book: The book is simple and introduces linear algebra concepts in a beginner-friendly manner. The first chapter explains linear systems, and the second describes vector spaces in detail. The subsequent chapters are about maps between spaces, determinants, and similarity. Again, this book is free to download, and you can access it using the above link.

If you are willing to shell some money from your pockets, you can also consider buying Introduction to Linear Algebra, 5th Edition.

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Is Coding required for Machine Learning?

One of the most common worries of a beginner in machine learning is understanding how to code. If you have never coded in a programming language, it might be a bit difficult for you initially and gradually, as you practice it by utilising the right resources, you will become good at it. Python is one of the most popular programming languages among machine learning enthusiasts, so we recommend you start learning as it is simple and open-source.

Book Recommendation: Python for Everybody by Dr Charles R. Severance

About the book: This book is your one-stop solution for learning Python from scratch. It introduces so many basic concepts of programming and only later moves ahead towards complex topics. The first ten chapters of this book are crucial for understanding Python. The following chapters explain slightly advanced topics. The best part about this book is that it has a few chapters in the end on data analysis in Python and SQL. So, for machine learning beginners, this book is a must.

Get FREE Access to Machine Learning Example Codes for Data Cleaning, Data Munging, and Data Visualization

Laptop Requirements for Machine Learning

So many machine learning enthusiasts worry about investing in high-end technology-based laptops that are pretty expensive. The truth is that one doesn’t need to shell a lot of money on such expensive machines. We are living in the generation of cloud computing, and you can thus buy a basic laptop and implement your machine learning codes over the cloud. 

In case you are very much interested in purchasing a laptop for implementing ML projects, here are the characteristics the laptop should have:

  • Processor: Intel 8th (/higher) Gen or AMD 3rd Gen

  • RAM: At least 8 GB

  • Bus Speed of RAM: 2666 MHz or higher

  • Cache Memory: At least 8 MB

  • Cores: At least 4

  • Threads: Minimum 8

  • GPU: Nvidia GTX 1650 or higher

  • SSD Memory: At least 512 GB

Now that you are aware of the prerequisites for machine learning, it would be a good idea to explore the skills required for becoming a professional in machine learning. These skills will help you in understanding how the prerequisites are utilised by machine learning professionals in completing their daily tasks.

Machine Learning Required Skills

Just like the prerequisites, the skills required to become a machine learning engineer are not biased towards a particular domain. You can verify this by looking at the skills mentioned below.

  • Performing predictive analytics on the given dataset using any one of the popular computer programming languages like Python, R, Julia, etc.

  • Using statistical tools on the given dataset to reveal insightful conclusions.

  • Creating your dataset through data mining and implementing machine learning algorithms over them.

  • Optimising the accuracy of a machine learning algorithm.

  • Applying Exploratory Data Analysis techniques over the dataset to extract information from it.

Recommended Reading: 15 Top Machine Learning Projects for Final Year Students

After the prerequisites list has been covered by a beginner in ML, a question that is natural to ask is what should be the next step. We have answered this exact question in the next section.

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Can I Teach Myself Machine Learning?

Yes, yes! It is very much possible to learn machine learning by yourself. All you need is the right set of resources to learn. We have already listed free books above that will prepare you for learning machine learning. Your next step should be to work on a few machine learning projects to understand how all you have learned is implemented practically. And in case you are searching for such a platform that teaches machine learning from scratch through solved projects, you are on the right page because ProjectPro does exactly that.

At ProjectPro, we design industry-relevant projects that can give the perfect push to freshers in machine learning before they join the professional world. The projects will prepare them for the practical problems that machine learning engineers solve daily. We provide a generic learning path for beginners and also offer customised learning paths for our users if they have specific needs. For intermediate professionals like software developers who want to transition from Programming to Data Science, they too can benefit from our solved end-to-end projects.

prerequisites for machine learning

The project solutions are presented in a series of short videos. The first few videos provide a business overview of the project; the following videos discuss that dataset and the solution of the business problem at hand. The videos are short and to the point. And, if you thoroughly enjoy solving problems by actively participating in the methodology, you will enjoy learning machine learning through guided videos as they contain a step-by-step approach to designing the code. New projects are added every month to the repository to help learners stay abreast with the recent trends and developments in the tools and technologies used by industry experts. So, if all this sounds interesting to you, we recommend you check out the following beginner-friendly machine learning projects from our library.

  1. Predicting survival on the Titanic
  2. Build a music Recommendation System Python using ML
  3. BigMart Sales Prediction Solution using Python
  4. Kaggle Instacart Solution
  5. Credit Card Fraud Detection 
  6. Churn Model using logistic regression
  7. Walmart Store Sales Forecasting 

Suppose you are willing to upgrade and interested in traversing through different technologies in Data Science. In that case, you may want to check out other categories like NLP Projects, Deep Learning Projects, TensorFlow Projects, Big Data Projects, etc., that are there in our repository.

Recommended Reading: How to learn NLP from scratch in 2021?

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FAQs Related to Prerequisites for Machine Learning 

What are the prerequisites for a machine learning course?

The prerequisites for a machine learning course include a stronghold of linear algebra, calculus, programming skills, probability, and statistics. Most of the topics can be quickly understood while working on solved projects by ProjectPro that resemble how solutions are implemented in the real world.

Do you need to learn python before machine learning?

It would be a bonus if you knew beforehand how to code in the programming language, but it is not mandatory. Python is a high-level programming language and can be quickly understood by a user. So, one can easily learn it simultaneously while working on projects.

What are the requirements to learn machine learning?

Basic knowledge for machine learning includes linear algebra, calculus, programming skills, probability, and statistics. Along with these, you will need a decent laptop to implement machine-learning-based solutions.

 

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About the Author

Manika

Manika Nagpal is a versatile professional with a strong background in both Physics and Data Science. As a Senior Analyst at ProjectPro, she leverages her expertise in data science and writing to create engaging and insightful blogs that help businesses and individuals stay up-to-date with the

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