Topic: Seven Steps to master in machine  learning using python 

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  • May 21, 2021
  • Machine Learning

What is python??? 

Dating from 1991, the Python programing language was considered a gap-filler, how to  write down scripts that “automate the boring stuff” (as one popular book on learning  Python put it) or to rapidly prototype applications which will be implemented in other languages. 

However, over the past few years, Python has emerged as a first-class citizen in modern  software development, infrastructure management, and data analysis. it’s not a back room utility language, but a serious force in web application creation and systems  management, and a key driver of the explosion in big data analytics and machine  intelligence. 

Python is straightforward to find out and use. The number of features within the  language itself is modest, requiring relatively little investment of your time or effort to  supply your first programs. The Python syntax is meant to be readable and easy. This  simplicity makes Python a perfect teaching language, and it lets newcomers pick it up  quickly. As a result, developers spend longer brooding about the matter they’re trying to  unravel and fewer time brooding about language complexities or deciphering code left by  others. 


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What is machine Learning??? 

Machine learning (ML) is that the study of computer algorithms that improve  automatically through experience and by the utilization of knowledge. it’s seen as a  neighbourhood of AI. Machine learning algorithms build a model supported sample  data, referred to as “training data”, so as to form predictions or decisions without being  explicitly programmed to try to so. Machine learning algorithms are utilized in a good  sort of applications, like in medicine, email filtering, and computer vision, where it’s  difficult or unfeasible to develop conventional algorithms to perform the needed tasks. 

A subset of machine learning is closely associated with computational statistics, which  focuses on making predictions using computers; but not all machine learning is statistical  learning. The study of mathematical optimization delivers methods, theory and  application domains to the sector of machine learning. data processing may be a related  field of study, that specialize in exploratory data analysis through unsupervised learning.  In its application across business problems, machine learning is additionally mentioned  as predictive analytics. 

Machine learning is one among the recent buzzwords immediately and has been  experiencing its expansion and recognition in recent years. But there’s a scarcity of 

skilled Machine Learning professionals within the market and it’s an excellent time to  kick start your career within the machine learning field. this text aims to offer you an  introductory guide to start out your machine learning journey with Python in 7 steps.  

Because Python is taken into account to be within the first place within the list of all ML  development languages. So let’s start!! 

Step-1 Basics of python: 

Maybe you’re thinking you would like to be an expert in Python for proceeding in  machine learning. Well, this is often not true. In fact, Python makes your path to  machine learning easier. you would like to possess an honest command over the  fundamentals of Python. 

Along with this, do install an editor or IDE for Python in your machine. There are many  IDEs available. Like, Jupyter-notebook, Spyder, Pycharm, VS Code. You can select any  one of them. 

Step-2 Foundation of machine learning: 

To the beginners, machine learning seems to possess many new high-technical concepts  and processes. If you think that so, then you’ll feel glad to understand you’re wrong.  Machine learning is predicated on the elemental subjects which we studied in our  college. ML isn’t a troublesome job. 

For mastering machine learning you need to be proficient at following points: 

  1. Statistics 
  2. Programing Languages 
  3. Mathematics 
  4. ML Algorithms 
  5. Data Analysis 
  6. Web Scraping 

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Step-3 Packages needed:  

Here comes the hero of the image, Python packages. this is often the first reason why the  name of Python is crazy machine learning. After performing on the prerequisites  mentioned above, realize the Python libraries which are used for ML. 

Though in-built Python libraries are quite enough for machine learning but, you’ll also  import required libraries from outside. NumPy, Pandas, Matplotlib, Scikit-Learn are the  libraries that are widely utilized in ML.

Step-4 Python with machine learning 

Moving ahead on the trail of machine learning, subsequent topic you would like to figure  on is data pre-processing and machine learning techniques. In machine learning, we  don’t require data, we require quality data and for this, data pre-processing is required. 

  1. Data pre-processing 
  2. Data Analysis 
  3. Visualizing data plots 

Machine learning techniques are the strongest weapons for machine learning. many of us  think that ML techniques and algorithms are an equivalent. But this is often absolutely  wrong. Techniques are the thanks to solve a drag and once we mention algorithms we  expect output from the given input. 

Here are some techniques which will take you closer to your destination.  Supervised Learning  

  1. Regression 
  2. Classification 

Unsupervised Learning 

  1. Clustering  

Market Basket Analysis 


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Step-5 Machine learning algorithms: 

Machine learning algorithms are the backbone of machine learning. What does make a  machine smart? in fact algorithms. A machine behaves consistent with the algorithms. I  suggest, before getting them with Python, understand these algorithms theoretically.  Then proceed towards its practical implementation with Python. 

Look some algorithms makes it influential technology 

Linear, Multiple Linear, Polynomial and Logistic Regression 

Decision Tree Classifier and Regressor 

Support Vector Machine Classifier and Regressor  

Naïve Bayes 



K-means Clustering 

Hierarchical Clustering

Step 6: Some advance topics to know: 

A journey becomes interesting when there are adventures. Sarcastically, in our journey,  the adventures are close to come. After the algorithms, now its turn of the advanced  machine learning concepts which can cause you to better in classification. So,  welcoming our adventures which are support vector machine (SVM), Dimensionality  reduction, and gradient boosting algorithm.  

Step7: Deep learning with python: 

Deep learning with Python is another aspect of machine learning which is driving  everyone crazy. And when Python is added to deep learning, then it becomes fun to  figure on such methods. Before learning it with Python, first, understand what’s deep  learning

Aniket R. Thorave

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