You don't need to know complex math to get started with machine learning!

In this thread we will take a look at a step by step guide on how you can train a simple machine learning model in under 10 minutes.
( without any of the complex math )

> The point of this thread is to help you get started with machine learning, not to proclaim that math is not important. However you don't need math to start machine learning.

You can pick the up the math as you go deeper into machine learning.

For this exercise, you'll need to know basic programming in Python.

Let's begin

Here's our problem,we are given data in which we are given the number of flats in a house and its corresponding price. Like a house with one flat is worth 10000, and 20000 for a house with 2 flats.

We can clearly tell that the price of the house increases by 10000 per extra flat however our computer does not know this and we won't it tell it about this, it'll have to figure things out on its own

Here's the code

https://colab.research.google.com/drive/1FxSrY6hwdgszzNydyobTLsMyO0bfpiPs?usp=sharing

Let's try to understand what is going on here

1. We import TensorFlow and Keras which are frameworks for making neural nets

2. Our Neural Net: This is where all the magic happens, for this exercise we need only one neuron.

Wait! What is a neural net?

Neural Networks are a digital imitation of the neurons you see in the human brain.

In these neural networks, data flows through them and each neuron (the circle) has a numerical value which will change.

The value of a neuron gets changes to something which is close to what we want each time the data passes through the neural network.

Think of the neurons as dials on a lock, you have to tune every dial to open the lock.

It is almost impossible for a human to tune thousands of dials like these, but a computer certainly can.

Once the dials are well tuned, you have a well trained neural network!

In this case we'll be able to predict the prices of houses based on how many flats they have.

Moving on.

3. Now we pass the data (flats and prices) through our neural network 500 times. (these loops are called epochs)

4. Finally,we predict what the price of a house with 10 flats. (we should get something around 100,000)

And that's it!
It was that easy.
In case you want to improve your python skills after this exercise, these are great courses to take https://twitter.com/PrasoonPratham/status/1320604117459296257?s=20

Here's a thread which you might be helpful to you. https://twitter.com/PrasoonPratham/status/1324608987518529536?s=20