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Getting into Machine Learning using Python

Every day, new breakthroughs are changing what's possible with computers. Do you think it is an organization stuff or only top coders can do that? Let’s break this thought and get dived into Machine Learning using the most loved language among coders.

Did you ever wonder that you are getting advertisements of things you recently browsed from your browser? Well, Machine Learning is the answer to it.

Google AdSense continuously tracks the activities from your browser and identify what do you try to search and browse the most. The advertisements are displayed on the basis of this calculated stuff.

Ever tried to unlock your mobile phone using your face? Even smartphones use machine learning for the same. There are many examples in our daily life that use machine learning, including Face Recognition Attendance System, computer games like chess, etc.

Technically, “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.”

Well, in this blog, we shall learn about how to get hands on into machine learning using Python.

Python is FUN!

If you are new into the coding and development domain, Python is a perfect start to grab things quickly and efficiently. It is a high-level, object-oriented, interpreted programming language, which has caught worldwide attention.

To learn the basics of Python sentdex is perfect for you. There are few people who are not able to catch-up with this, so alternatively you can go for Programming for Everybody (Getting Started with Python).


Once you are done with the basics it’s time to know important packages in Python for machine learning.

Libraries are IMPORTANT! Don’t Forget

Libraries are of great use in any programming language. Few libraries are very important for Machine Learning

  • scipy - SciPy is a free and open-source Python library used for scientific computing and technical computing. It is distributed under the BSD licensed library to perform Mathematical, Scientific and Engineering Computations.
  • numpy - NumPy is a Python package which stands for ‘Numerical Python’. It is the core library for scientific computing, which contains a powerful n-dimensional array object, provide tools for integrating C, C++ etc.
  • pandas – It is a software library written for the Python programming language for data manipulation and analysis.
  • matplotlib - Matplotlib is a python library used to create 2D graphs and plots by using python scripts.

So, we are done with learning Python Software Development, important libraries to learn Machine Learning. Now it’s time to dive into the track.

Machine Learning Courses – At their Best!

You can find a number of courses online on various websites like Coursera, edX, Udacity, Khan Academy, Udemy, DataCamp, etc. But the search is often endless for finding the best course. The best course for Machine Learning in my opinion is – Machine Learning by Andrew Ng. This is an 11 weeks course where you can learn from the


basics of Machine Learning to its advance. All the tutorials are taught in detail and coding is preferred in MATLAB. This course is important for the detailed theoretical understanding of ML, it’s types, Neural Networks, algorithms and the mathematical proofs of the algorithms. The course has an automated tool that generates your marks once you submit your answers. The course is offered by Stanford and carries prime importance.

Once you are done with this course, the next one that comes is - Applied Machine Learning with Python by University of Michigan. This is a 4 weeks course that focuses on practical Python implementation of Machine Learning algorithms that you learnt. You will get to know the practical use of the libraries that I mentioned at the beginning.

If you are interested to learn even more and want to jump into deep learning, you must refer to the Deep Learning Specialization. This is provided by the Deeplearning.ai, Founded by Andrew Ng.

DataCamp is also a great platform to learn the concepts of Data Science. It has partnered with Facebook to provide scholarship to people around the world for Data Science courses worth $300. This is an initiative by the Developer Circles of Facebook. If you are not a part of Developer Circles, you can find a circle near to you here.


Courses are so costly!

Yes, all the courses are quite costly, but they are worth it. Not everyone is capable to pay this amount to get a verified certificate. You can apply for a Financial Aid for the course. Once you have submitted the application of Financial Aid, if takes upto 15 days to get reviewed. If it is accepted, ENJOY! You have got the course for free.

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