Machine Learning: A Gentle Introduction

Machine Learning: A Gentle Introduction

Credits to edureka!


Machine Learning is probably one of the most interesting and hyped branches of computer science. But, What is ML? What does it do? And what makes Machine Learning so popular? Don’t worry we’ve got you covered. But before you proceed it is advised that you know python, if don’t know Python you can learn it from our Python Tutorial Series.

What is ML?

The thing that seperates Humans form machines is the fact that humans learn from their expiriences. But is it possible to make a machine learn?

And The answer is Yes!

Machine Learning is a subdomain of Artificial Intelligence in which algorithms improve on their own through experience. And this expirience is nothing but Data. Data is the lifeline of ML, quality of data can significantly affect the performance of your model. That’s why a good to know how to manipulate data.

How ML works?

Let’s understand this with an example. Imagine there are 5 houses with following specification:-

Area of the House(in square feet)Price of The House(in ₹)
1000120000
50060000
80080000
900100000
1500180000
This data is fictional

Let’s assume for now that Price of a house is solely determined by the Area of the House. So, what would the price of the house of area 120000 square feet? Based on the data above, we can say that the answer lies somewhere in between ₹120000 to ₹180000. After thinking for a while we might be able to pinpoint the price too. But how will you make a machine make a guess?

To understand that let’s plot the data on a graph:-

Scatter Plot of House Data

Now once the machine have this data plotted on the graph. The ML model will improve itself and find the best fit for the line in the curve such that each point on the line, i.e. (x,y) where x is the area of the house and y is the predicted price of that house, this line will be fitted in the plot in such a way that the predicted values are nearer to the actual values. The Line will look something like this:-

Line on the plot

Now for the above line the value corresponding to x(Area) = 1200 is y(Price) = 140451.

The above method is something called Linear Regression. Which we’ll learn about more in this series. But how did our model learn that this particular line is the best fit?

How did it find the line?

Now before learning how did it find the line let’s understand what a line is? A Line is exactly what it says, A LINE. But Mathematically, Line is an equation of form:-

y = mx + c

Now, what the model will do is that it’ll start with random value of m and c and since these are random values it could be anything, let’s say m = 300 and c = 9000. Next let’s plot this line on our scatter plot:-

Hmm, this line doesn’t look like it’s predicting the values accurately. So what now? Now the line will take our data as input and update the value of m and c such that the line is the best fit to the scatter plot. The in-depth math on how to get the best values for m and c will be explained in the linear regression section but just to feed your curiosity we find the best m and c (or sometimes referred as a and b) by a method called Ordinary Least Squares. We’ll discuss this further in the series too.

What makes it special?

Now you might be wondering whats so speacial about ML, all it is is just mathematics at play. And you are mostly right, ML is Math in its core. But even though the above algorithm is the most basic one, the fact that the same algorithm can improve itself to fit itself for the given data is what makes ML special. You just feed the data to the algorithm and the algorithm will improve on its own. And that is why ML is special, you don’t need you redesign your algorithm according to data, you just need the data and leave the improvement to ML.


Also Read:


  • How to Ace Your Machine Learning Assignment – A Guide for Beginners
    Introduction to Machine Learning Assignment Help WhatsApp us for any type of help in your assignment related to machine learning or any other assignment. Are you studying machine learning and struggling with your assignment? You’re not alone. Many students struggle with assignments when they first begin a machine learning class, but it’s not impossible. This…
  • Top 10 Resources to Find Machine Learning Datasets in 2022
    Datasets are essential to source the correct information for the work. To source the Machine Learning Datasets datasets, it is first necessary to know where you can get them. You must register for machine learning training for more expertise and knowledge on this topic. This article will discuss the top 10 sources from which you…
  • Face recognition Python
    In the Face recognition python article, we are going to build a project using which anyone will be able to detect faces. Have you ever noticed that Facebook automatically tags your friends when you try to upload a group photo? It can identify an individual using their face and this is one of the exciting…
  • Hate speech detection
    In this article, let’s build the Hate speech detection project in Python. In the current era of the Internet, it is obvious that almost everyone has social media apps to connect and interact with people around the world. At the same time, social media is a place where a lot of personal opinions have been…
  • MNIST Handwritten Digit Classification using Deep Learning
    In this article, we are gonna build a cool project which is the MNIST handwritten digit classification using deep learning. Even if you have little knowledge of deep learning this project will help you understand the concepts better and in a simple way. With that note let’s start building the project. Handwritten digit classification The handwritten…
  • Stock Price Prediction using Machine Learning
    Introduction One of the most challenging tasks is predicting how the stock market will perform. There are so many variables in prediction — physical vs. psychological, rational vs. illogical action, and so on. All of these factors combine to make share prices unpredictable and difficult to anticipate with great accuracy. Also, the most significant use…
  • Control Mouse with hand gestures detection python
    Introduction Gesture Controlled Virtual Mouse makes human-computer interaction simple by making use of Hand Gestures and Voice Commands. The computer requires almost no direct contact. All i/o operations can be virtually controlled by using static and dynamic hand gestures along with a voice assistant. This project makes use of state-of-art Machine Learning and Computer Vision…
  • Traffic Signal Violation Detection System using Computer Vision
    This is software for the practice of developing a system from completely scratch. Understanding this will help a lot in system development and the basic structure of a system, computer vision, and GUI with python library Tkinter, and basic OpenCV. Go here if you don’t have time. Motivation This project is made for the third-year(OR FINAL YEAR)…
  • Deepfake Detection Project Using Deep-Learning
    Deepfake Detection Project Description We have presented a deep fake face recognition system using neural network layers and various algorithms in the python programming language. Since our model is very bulky in size because we are Cloning various GitHub repositories along with the installation of various tarballs. It is advisable to use google Collaboratory for…
  • Employment Trends Of Private & Government Sector in UAE | Data Analysis
    DATA DESCRIPTION We have chosen the dataset related to various career fields in different emirates in various years. We will explore the various career opportunities to find deeper insights. We have chosen this dataset because employment is the primary concern in any nation. It is necessary for the government to keep a check on various…

Share:

Author: Herumb Shandilya