Steps To Successfully Learn Machine Learning

The growth and development of artificial intelligence is going to be incredible in the future. Many industry experts and consumers have stated that the artificial intelligence and the Internet of Things (IoT) will be the next industrial revolution or the next internet because it will be the future way in which businesses, consumers, and governments will interact with the physical world.

Machine learning is a method of data analysis, which automates analytical building. Using algorithms that iteratively learn from the data, machine learning allows the computers to find the hidden insights without being explicitly programmed where to look.



The importance of machine learning in Internet of Things (IOT)

Internet of Things generates an incomprehensible amount of data. It is predicted that by 2020 there will be 50 billion devices connected to the internet, generating Exabytes of data. Machine learning will play an imperative role in aggregating this data by using sophisticated algorithms, which are designed to identify the patterns from which new information can be fostered.

What's required to create good machine learning systems?

• Data preparation capabilities.
• Algorithms – basic and advanced.
• Automation and iterative processes.
• Ensemble modeling.
  
  
  

Start teaching machine learning yourself and be a professional machine learning engineer

These steps will be helpful to you to learn machine learning yourself at a beginner level.

Step 1

Getting started

• Find out what is machine learning and do research on it.
• Find out the skills to become a machine learning engineer.
• Interact with the experienced persons on social media and technical sites etc.
• Attend the workshops and conferences on machine learning and artificial intelligence.

Step 2

Learn Mathematics and Statistics

• Start learning Descriptive and Inferential statistics.
• Learn Probability.
• Learn Linear Algebra.
• Learn Multivariate Calculus.

Step 3

Select Your Tool

• Start learning Python or R programming language.
• R is easy to learn if compared to Python.
• Learn data analysis. You can also watch tutorials on Udacity.
• Make small projects, using any of the languages listed above.

Step 4

Watch Basic and Advanced Machine Learning Tutorials

• Machine learning course by Coursera.
• Machine learning classification by Coursera.
• Intro to machine learning by Udacity.
• Blogs and guides like Shout Future, machine learning mastery, etc.

Step 5

Build your profile

• Start your GitHub profile.
• Start practice in Kaggle competitions.

Plan well and follow the steps given above. It will take a long  time to become an expert machine learning engineer. Thus, start that job beginning from today.

References

• https://channels.theinnovationenterprise.com/whitepapers/95-the-importance-of-machine-learning-in-the-internet-of-things
• https://www.sas.com/en_us/insights/analytics/machine-learning.html