What is machine learning?
Machine learning is considered as a subset of artificial intelligence, which provides machines with the ability to learn without being explicitly programmed. Industry experts are predicting that the combination of Machine learning and hence artificial intelligence and Internet of Things(IoT) will be the new technological era setter and the business, startups, governments etc. will invest huge numbers in the same.
The oil of machine learning is the data. What do you mean by the data?
Data is familiar to everyone but not the insight inside the data. Machine learning analyzes the data and automates the analytical building. Machine learning is using mathematical algorithms and iteratively learning with the data. Hence, it finds an insight (something meaningful) from the data.
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Machine learning and IoT
The present decade is ruled by smartphones and it is obvious that IoT will rule the next decade or maybe the rest of the century. Nearly $6 trillion will be spent on IoT solutions over the next five years. The fact given above explains how the world looks as far as growth of IoT is concerned. Around 50 billion devices will be connected to the internet by the end of 2020. Machine learning will play an inevitable role in aggregating the data generated by the 50 billion devices by using sophisticated algorithms.
What includes a good machine learning system?
- Meaningful data and the preparation of the data.
- Mathematical algorithms.
- Automation and modelling.
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Machine learning - The phases
Machine learning is the hottest technology for the time being and investing your time and effort in the domain will be an asset. As a machine learning Engineer, I would like to classify the ML journey into 4 major milestones.
Step 1
Getting Started
- Gather an idea on machine learning, AI and IoT by reading blogs, attending webinars.
- Understand the possibilities and opportunities of the domain.
- Attend course by Andrew Ng on CourseEra.
- Attend courses conducted by CourseEra on data science.
- Explore Azure ML Studio documentation.
Step 2
Familiarize with Mathematics and algorithms
ML is all about the algorithms.Thorough knowledge of statistics and algorithms are mandatory to perform ML actions on the desired data. Focus on the fields given below.
- Applied Statistics
- Probability
- Algebra
- Calculus
Step 3
Select the infrastructure or tool
- The most powerful tool available for ML is Microsoft Azure ML Studio (https://studio.azureml.net/).
- Other tools available are H20, Tensor Flow, Scikit-Learn, Monkey Learn etc.
- R and Python are the most used languages for machine learning
Step 4
Create your profile and participate in competitions
- Create and update GitHub and BitBucket accounts.
- Practice and participate in competitions on Kaggle.
I came to know about ML just an year back and my interest lead me to the profession and for the time being, I am working in the best domain. Start exploring the world of ML+IoT.