What is Machine Learning?
For people working in the Technology Sector, it’s very rare that they have not yet heard of Machine Learning and Artificial Intelligence. ML and AI have been a buzzword from past few years but it has been in existence since the late 1940s but due to lack of computational resources and the world still in the cradle of technological advancement, there was not much that could have been done.
As we entered the 21st century powerful and cheap computational resources, massive advancement and growth in the technology sector and Zettabytes of data paved the way to explore the real power of AI and ML.
For people still not clear about what Machine Learning is: Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
Wait! What? without being explicitly programmed ??
Well there is programming but it is for training the Machine Learning Model on Historical Data, the data is fed to Machine Learning Algorithm to learn and later give predictions for some new set of data or future data.
We do not need to explicitly define rules for different cases, the model learns to give results for any of the cases provided it has been trained appropriately.
In a simple example :
A student is thought that 2+2 = 4, later if the student is given the task to add 4+4 he/she may not able to solve it because the student just knows 2+2 = 4 but have no idea what 4+4 is this is what we call a rule-based engine.
Another student is thought how to perform addition of numbers along with concepts of addition and train him on various types of addition operations instead of just teaching him 2+2 = 4, once student has learned the concept addition he/she can, later on, perform addition of any numbers without any mistake, this is what Machine Learning is.
Now let’s look at Simple Definition of Machine Learning
Machine learning is a subfield of artificial intelligence. Its goal is to enable computers to learn on their own. A machine’s learning algorithm enables it to identify patterns in observed data, build models that explain the world, and predict things without having explicit pre-programmed rules and models.
Some of the Domains of ML are Predictive Analysis, Forecasting, Natural Language Processing, Object Detection, Image Classification.
Chatbots, Anomaly Detection, Stock Price Prediction, Loan default prediction, Customer Churn and Lifetime Value prediction, Forecasting of future sales are just a bunch of applications of ML
There is so much to learn and explore in Machine Learning that you always feel like
But that’s what makes you more curious to explore and dive into the ocean of Machine Learning.
Data is the Key
As you may have noticed, the key component of this process is data. Data is the key to unlocking machine learning, as much as machine learning is the key to unlocking the insight.
The Data is fed to an Algorithm but before just passing the raw data to algorithm there a lot of things to be done like Data preparation, Data Cleaning, Feature Engineering, Data Analysis & Visualization, choosing the right algorithm and optimizing the algorithm, Training the algorithm on relevant data, Evaluating the accuracy of model and improving it further.
Types of Machine Learning
Machine Learning is further divided into
Artificial intelligence and Machine Learning will shape our future more powerfully than any other innovation this century. Anyone who does not understand it will soon find themselves feeling left behind, waking up in a world full of technology that feels more and more like magic.
I will Write and explore a lot more about Machine Learning and keep on sharing my knowledge with you guys. If you find this article useful let’s see how many claps can u hit in 5 seconds.
To understand the Basics of Machine Learning go here
For more interesting articles on Data Science and Machine Learning go here.