An Essential Guide on Machine Learning with Python for Beginners

An Essential Guide on Machine Learning with Python for Beginners

Learn Machine Learning Concepts Practically Using Python

It’s really wonderful to see that the man made things can think and make their own decisions over the problems. I still wonder how the insignificant species of pre historic time made an amazing history on earth by creating and optimizing the way of nature. Now we are advancing through trying to build something that can think like us. In my opinion, those who want to make their career in the field of machine learning or artificial intelligence are doing something done by the god or the nature. Because they are trying to make a new world of things with man made intelligence. I am not going to argue whether the concept is good or bad. I am just going to give you a brief introduction on the concepts of machine learning and how to solve the machine learning problems with various standard algorithms using my favorite programming language called Python.

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What you need to learn machine learning? A degree in Computer Science, certifications from various institutes or expertise in statistics and probability. No, you don’t need to have such a brain filled with lots of mathematics and coding stuffs. Only you should have is your passion towards learning. Most machine learning tutorials on the internet are focusing on the content which can only understandable by doctorates and experts in mathematics. I will try to reduce the hardness of the content as much as possible in this guide. If you are in purely beginning stage of these field, please consider reading some basic programming stuffs using the my other articles.

“A breakthrough in machine learning would be worth of ten Microsoft“ — Bill Gates

The Concept of Machine Learning

If you are familiar with any one of the programming languages in the world of computers, then you will have some experiences with inputs, outputs and the instructions given to the computer. In the traditional methods of problem solving produces the output with the help of given instructions to the machine. A very slight change makes the machine learning great for many purposes. The real problems are not always can be solved by normal traditional programming methodologies. Because we will have written the common statements for any kind of inputs. Even the result can be predicted without a machine by doing some calculations on paper. Literally, the traditional programs are acting like a calculator for complex and specified problem sets.

The machine learning differs in the instructions part. In machine learning we will give some data to a tool called model which will write a very efficient program for the data. You may wonder how a machine can make some decision on the problem solving instructions. The reliability lies on the data provided by the programmer. In the concept of machine learning the data given to the model consist of two things. One is input and another one is output. All problems need a solution. We are giving a model the sample inputs and their corresponding outputs to understand the pattern among the data.

Let us look at the agenda of the article.

:boom: What Machine Learning can do?

:boom: Types of Machine Learning

:boom: Learning concepts in a Baby’s perspective

:boom: Classification of machine learning problems

:boom: Regression

:boom: Classification

:boom: Clustering

:boom: A Data set explained

:boom: Qualities a data set should have

:boom: Machine Learning Workflow

:boom: Linear Regression

:boom: Logistic Regression

:boom: Support Vector Machine

:boom: K Nearest Neighbors Algorithm

:boom: Final Note