Machine Learning for Granny
Tags: machinelearning
Published: 2020-06-02 04:46:22

Explaining machine learning to granny was not easy you need to break down words and explain its meaning and answer all those curious questions just like a 5 years old kid. 

**What is Machine Learning?**
[Answering Granny's Question]
Machine Learning as the word suggests its teaching a machine. Just like a newborn baby, machines also need to be taught initially. 
Example:
When you have to teach a baby that call you grandma, what do u do? You keep going to her and point yourself and say aloud say, grandma. And you repeat this process for n number of times until one day the baby calls you grandma. 
Similarly, it's with machines they need to be fed with images and information you want them to learn and keep training them, and then it recognizes the image.

**How is Machine learning Helping Humans?**
[Answering Granny's Question]
Machine learning automates and eases a lot of human work. Also, it completes the work a lot faster and with fewer errors. 
Example:
You are making Mango pie and you have a room full of mangoes. Now, all the mangoes are unripe and some are over ripped, and to make the best mango pie you need the exactly ripped mangoes. So, you have to manually select the mangoes, and its a time-consuming process. Machine learning can help you with it, on training the model by feeding it with unripe, ripe, and overripe mango images. Now the model can help you classify the mangoes quickly into the 3 categories and then you can make your pie faster and with the best mangoes.
Machine Learning: It is an application of artificial intelligence (AI) that provides computer systems the ability to automatically learn and improve from experience, observations, and pattern analysis of a given datasets without explicit programming. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves and constantly adapt to new data and discover new patterns or rules in it.

**Types of ML**

*Supervised learning :*
Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input-output pairs. It is similar to the previous example where we initially fed the machine with the input-output pair and later the machine mapped the input to the output correctly.

*Unsupervised Learning :*
Let's take an example of a baby again, and the family cat. She knows and identifies this cat. A few weeks later a family friend brings along a cat and tries to play with the baby. Baby has not seen this cat earlier. But it recognizes many features (2 ears, eyes, walking on 4 legs) are like her pet cat. She identifies the new animal as a cat. This is unsupervised learning, where you are not taught but you learn from the data (in this case data about a cat.) Had this been supervised learning, the family friend would have told the baby that it's a cat.

*Reinforcement learning :*
Consider the scenario of teaching new tricks to your dog
As the dog doesn't understand English or any other human language, we can't tell him directly what to do. Instead, we follow a different strategy.
We emulate a situation, and the dog tries to respond in many different ways. If the dog's response is the desired way, we will give his favorite food. Now whenever the dog is exposed to the same situation, the dog executes a similar action with even more enthusiastically in expectation of getting more reward(food). That's like learning that dog gets from "what to do" from positive experiences. At the same time, the dog also learns what not to do when faced with negative experiences. This is Reinforcement learning.

**Advantages of Machine Learning**
1. Easily identifies trends and patterns
2. No human intervention needed (automation)
3. Continuous Improvement
4. Handling multi-dimensional and multi-variety data
5. Wide Applications

*Granny's Reaction*
Truly Machine learning is changing the world in a better way and I guess it will keep changing and new things will be invented to help mankind.