“AI doesn’t have to be evil to destroy humanity- if AI has a goal and humanity just happens to come in the way, it will destroy humanity as a matter of course without even thinking about it, no hard feelings.”

  • Elon Mask 

In this technology-driven world, you have already known two popular technical terms, “AI” and “Machine learning,”. But people don’t realize or at least don’t think, how AI is impacting our life. 

You will see AI applications everywhere, from self-driving and parking vehicles to digital assistants and from vehicle recognition identification to robots and transportation. Face recognition, search engine optimization, and so on.

Undoubtedly machine learning and AI are essential to understand. If you are tech-freak and keenly interested in machine learning and AI, you can now quickly learn it without spending any cost.

You may hire an assignment writer for your AI or machine learning assignment, but before that, have a look at this blog.  

What is machine learning? 

Machine learning or ML is a kind of artificial intelligence that allows a software application to become more specific and accurate at predicting outcomes without being explicitly programmed to do so. Instead, ML algorithms use huge database input to predict new outcomes. 

Recommendation engines are a common tool for machine learning. Technically machine learning is used for fraud detection, spam filtering, malware threat detection, business process automation, and predictive maintenance.

Machine learning is crucial because it offers you a view of trends in customer behaviour and operational business patterns. It also supports the development of new services and products. 

Most of the leading social media platforms like Twitter, Facebook, Instagram, and even the most significant search engine optimization, Google, use the latest machine learning and AI technology. 

Students or any newly interested individual can learn machine learning and AI for free. You need to develop deep knowledge in machine learning related basics and artificial intelligence-based technologies and programming languages.

Know the different types of machine learning:

Being naïve, you must know the types of machine learning. Let’s dig into four basic types of machine learning: reinforcement, supervised, unsupervised, and semi-supervised. This differentiation depends on the choosing algorithm by the data and IT analyst. 

  • Supervised machine learning algorithm works for various tasks, including binary classification, multi-class classification, regression modelling and ensembling. 
  • The unsupervised ML algorithm is used for clustering, anomaly detection, association mining and dimensionally reduction. 
  • Semi-supervised machine learning allows machine translation, fraud detection and labelling data. 
  • The reinforcement machine learning type offers robotics, video gameplay and resource management. 

Resources for learning machine learning: How to become a machine learning and AI expert?

Nowadays, you will find millions of popular sites, sources and E-books available online for learning machine language. 

You can start with Stanford’s machine learning course for a vast knowledge and intro to machine learning. It focuses on the elementary lessons on machine learning, data mining, and statistical pattern identification with explanation videos that are useful in clearing up the basic theory. 

For the next level of understanding of ML, you can go for a profound introduction to machine learning from MIT professors’ online, in-depth knowledge with PyTorch from the New York University professors. 

If you want a self-study guide to machine learning, you can also learn it from Google. Yes! This tech giant offers various online courses on machine learning and AI. 

Many online crash courses online are also available where you can register your name for free/ 

Read complementary online articles.    

It has been scientifically proven many times that the human’s brain learns better by repeating and learning in multiple ways, including visually, audibly, and reading by themselves. As reading needs the most concentration, learning from books is still an excellent option for students. You will get great recently published articles on machine learning and AI by searching them on Google. You will be amazed that most tech gurus and current CEOs have predicted the future of machine learning and how it can change your career!!

Here are some article references you will get for free. Before you dive into the books, coding or online courses- these are the most-read articles:

  • Machine learning for beginners: An introduction to Neutral networks by Victor Zhou 
  • Understanding neural networks by Prince Cinema 
  • What is Machine learning? By Roberto Iriondo
  • The 80/20 AI Reading list by Vishal Maini 
  • A sorted reading list for new MILA students      

Read essential books

This tip is optional for students. If students acquire the patience to read and understand machine language and AI, they can read books. It will always give you a great background explanation. Most of the books. Here is the list of free books to avail of from the internet.

  • Deep learning book 
  • Probabilistic machine learning 
  • Dive into a deep understanding of ML
  • Mathematics for machine learning 
  • Pattern recognition and machine learning
  • The elements of statistical learning  
  • Understanding machine learning: From theory to algorithms by Shai Shalev and Shai Bec-David        
  • If you don’t have any math background, which is an imperial part of machine learning and AI knowledge- this is the list of free online tutorials available on YouTube:
  • Linear algebra 
  • Mathematics for machine learning by Garrett Thomas 
  • Statistics and probability 
  • Multivariable calculus 
  • Mathematical monk 

Apart from all these sources- you can also join various Facebook communities to share your problems. These communities or LinkedIn groups are helpful while getting suitable answers working on machine learning and AI. 

Join Facebook groups named Artificial intelligence and deep learning

Deep learning      

If you want to be more guided and have vast knowledge, these courses are the perfect options for you:

  • Deep learning specialization By Andrew Ng
  • Machine and AI engineering by IBM professional certificates
  • TensorFlow certified course 
  • AI programming with python 
  • Fast. Ai’s deep learning courses      

Image source: https://www.pexels.com/photo/robot-holding-a-spoon-8386435/

How to Practise Machine Learning?

This is a vital alarm for you—most of your time taking part in data gathering, cleaning, integration, and pre-processing. You must practice with this because you need a high-quality database. But working with a large amount of data can be daunting for you!

So, this is where most of your time will go! 

That’s why students should learn multiple models and practice accurate data. It will help you create your prediction around which types of models are suitable in various situations. 

Besides it, it is also significant to understand how to understand the results obtained by using various models.

This is easy to do if you know multiple parameters and regulation methods applied to models.  

Conclusion:

After gaining enough knowledge on machine learning and AI, you can apply it in your professional career. You are now on the way to becoming a machine learning expert. But yes, you have to continue your learning process and take new challenges to adapt yourself to this tech-driven world!