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We Are Here To Help you to start Applied Machine Learning and Artificial Intelligence.

Below is the list that you have been looking for!


  • Understand Data First
  • Learn Various ML Concepts
  • Apply ML Algorithm With Python


  • Understand Deep Learning
  • Study Research paper and apply
  • Contribute to society



Makeup Your mind

From childhood, we are forced to choose who we are. We are always focused on fixed goals, the more we remain folded in our field the better expert we are. Every small step matters the most with full dedication and enthusiasm.

A self believe is the most powerful tool to nourish yourself. I have always admired this flow chart, This is my belief all philosophy relies on this boundary.

problem flowchart picture credit

I feel you are limiting yourself because, you think, you can’t start without prior knowledge, hmm…

Lemme guess you are thinking about Statistics, alright let me be very clear you just now started, don’t even think about this as you are just scratching the surface, everything will come into you step by step.

I will not be lying to you, it will take some time but if you keep on learning and practicing soon you will get the right result and the best part of your journey will be you will be so proud of yourself for achieving your goal, and this will not limit in one aspect of your life it will enhance you in all direction, it will open your mind and you would have a broader perspective to look into your issue.

Go in with the right mindset

There are two ways to approach new learning, Some go in wanting to learn it, while others go in wanting to master it. It’s all about doing well, and discovering your natural talent, don’t think too much about, “how I am going to do this”, or “I am going to make the mistake”. This is not meant for me, This is not my cup of tea.

All negative thought comes and goes, it all depends on the present day. but if you keep on thinking about this again and again definitely, you will get a good seance of small out of it. This case is not only with Machine learning it used to happen everywhere. This could be Arts or Sports Because the human brain is meant to be with positive and negative thoughts. It balances you to test yourself in different situations. It all depends on how you train your thoughts. We do the same in Machine Learning, we train the model with unbiased datasets.

The steps are very simple, you start reading an article about Machine Learning. Don’t think too much about which one is good and which one is not. As soon as you start reading and understand the nuances of your learning, you start analyzing those articles. And sooner you will get to know which one is to follow.

Understand The Prerequisites

You can start machine learning directly but there are some introductory concepts that will help you to understand the scene behind the black box, that’s what we use to call it, “Model is a black box”.

  1. Python for Data Science
  2. Basic Data Visualization in Python
  3. Basic Linear Algebra
  4. Probability for Machine Learning
  5. Statistics for Machine Learning

Be Focus

Learning is an art, everyone has their own style of understanding. you need to understand why this is so important. You have to strategies your learning. Spend at least 2 hours daily on your learning, yes that’s all you need to do. Start with the prerequisite list that I have given. Then switch to enhance your skill with a Machine learning algorithm.

Follow and observe the trends, and how technologies improve life. Discipline is very important in learning, I am not saying you have to work hard but work smart. But spend at least 2 hours daily, and you will see the improvement. Sooner you will start picking the Machine Learning Jargon.

So be with yourself, don’t lose focus. Sooner or later learning always helps in your life. follow my blog

Python for Data Science

Python Installation

You will need various Python packages or libraries for specific purposes. Anaconda is an open-source distribution that simplifies package management and deployment. Use Anaconda to install Python as well as the packages, since it comes pre-loaded with most of the packages you’ll need.

Advantages of using Anaconda

  • Easy to manage and get started with most requirements for ML/AI problems
  • Anaconda comes with many libraries such as NumPy, OpenCV, SciPy, PyQt, the Spyder IDE, etc.

Anaconda can be downloaded from There is no need to download Python separately the Anaconda installer will do this for you. You’ll use the Jupyter IPython Notebook as the main environment for writing Python code. The main advantage of using the Jupyter Notebook is that you can write both code and normal text (using the Markdown format in Jupyter) in the notebooks. These notebooks are easy to read and share and can even be used to present your work to others. you can follow this Jupyter Link.

Python is a widely used language for many purposes web application, data analysis, OS programming, etc. There are a lot of libraries available for Python, pretty much everything that you can think of.

Basic Data structure

Start with the Basic Python Data structure. follow my GitHub repository This repository contains the Jupyter Notebook for the below list of data structure and control structure and functions.

  • Data Type
  • List
  • Set
  • Tuples
  • Dictionaries
  • DataStructure Reference

Control Structures and Functions

Control structures are the essence of programming since they help computers do what they do best — automate repetitive tasks intelligently. The most common control structures are if-else statements, for and while loops, and (specific to Python) list and dictionary comprehensions. This session will cover all of these.

  • Control structures
    • If-elif-else
    • For loop
    • While loop
    • List comprehension
    • Dictionary comprehensions
  • Functions
  • Map
  • Filter
  • Reduce
Additional Reading about Python

Data Visualization

The picture is worth a thousand words. You can describe data and its properties verbally in as much eloquent detail as you like, but a picture is always more valuable. Humans learn and understand through visual cues, and there is nothing better than an image to explain a concept or an idea.

There are two important toolkits and libraries in order to perform the Data visualizations in Machine learning. These libraries are written in Python.

Once your toolkit is equipped with these libraries, you can perform most types of visualizations. 

So I have prepared for you a few Python notebooks that can give you a basic understanding of visualization. This notebook also gives you an understanding of why visualizations are a critical part of a data analyst’s skillset.

Data Visualization GitHub

Basic Linear Algebra

Following are the main areas that you need to study in order to understand the Machine learning model.

  • Vectors & Vector Spaces
  • Matrices
  • Linear Transformations
  • Eigenvectors/Eigenvalues