Day 4: Before We Start! || ML Crash Course


Day 4: Before We Start! || ML Crash Course



We are very close to learning our first form of Classical Machine Learning which is Classification. However, before starting it we need a skeleton to work on. That skeleton is provided by python. There are mainly 3 languages for ML Development: Python, R & AIML. R is a bit complex and AIML is not widely used so we go with one of the most trending languages right now, Python. In this course, we will install Python and all its depenencies all at once to give a headstart.

Hey Guys! This is Manas from – “Your one stop destination for everything computer science”.

Basic Modules in ML

In Python we need a few basic modules these are present in almost every ML Experiment. The most common Module is Numpy which is used for computation and math. Tensorflow, Tflearn, sklearn, scikit-learn, Keras, pytorch, pybrain all follow suit. These are various Machine Learning & Deep Learning frameworks that make your programming easier. Keras is one of the best Deep Learning modules out there! Keras is basically a wrapper for Tensorflow that makes coding for Deep Learning much easier.

Installation Procedure

Firstly, we need a good Python Environment to work with. We can use the standalone Python environment provided by but it just isn’t good enough for the job as we need to manually install most of the packages with pip. This is not worth our time. We have a Python Environment that is specifically built for Machine Learning tasks which comes with all the important modules pre-installed. This Environment also serves as a development platform and it is called Anaconda. Anaconda 3 to be specific. You can download the setup file from

I wont show you the installation process as it is fairly intuitive. Expect and installation time of 8-10 Minutes. Be sure to add the python path variable to the Environment Variables. For more in-depth coverage search “how to install Anaconda 3″ on YouTube.

After this, we need an IDE(Integrated Development Environment). We could have used IDLE given by Python but that lacks certain features and doesn’t look soothing to the eye. I would suggest you to start with either,

Once this is done we are ready! Since we have installed Anaconda, all the modules will be installed automatically. Now it’s just a matter of writing your code and importing the modules. Remember the location where your Anaconda folder has been installed, inside the folder you will find the python interpreter. We will run our programs from this interpreter.

Now you are all set to learn Machine Learning and We are about to start Classification – “The stepping stone into ML”.



Manas Hejmadi

I am a boy who studies in 9th grade at Bangalore! I have a good knowledge of computer programming, AI and UI Design. I aspire to create a tech startup of my own!

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