Three Reasons Why Machine Learning Learners Should Use Python


This is an edited version of the "** Kikagaku Online **" article for Qiita.


This time, for those who are thinking of studying machine learning from now on, I would like to tell you which programming language you should study in.

Although it is already mentioned in the title, my recommended programming language is ** Python **.

Why should Python be used among the many programming languages out there?

Here are three reasons why!

1. Abundant libraries that can be used for machine learning!

Programming is usually rarely written by yourself from scratch.

Then, what to do is that I often write using ** libraries ** and ** frameworks ** that are open to the world.

For example, when creating a web service using Python, it is created using a web framework called Django.

Machine learning is the same, and most of the time we program using libraries.

Most major programming languages have libraries for machine learning, Among them, it can be said that ** Python's machine learning library is outstanding in terms of abundance and achievements **.

I will list some related libraries, so please check them out if you are interested.

Library Description
scikit-learn A library of many machine learning techniques.
TensorFlow A deep learning framework developed by Google.
NumPy Library for numerical calculation. It can be calculated at high speed and is often used for machine learning where the calculation time is severe.

2. You can do it all at once until the service is released!

Other programming languages are also suitable if they are for machine learning only or for research purposes only (such as MATLAB).

What makes Python different from those languages is that you can use machine learning ** to publish services all at once **.

Python is so widely used in the web world that There are many web frameworks such as Django that I mentioned earlier.

By using these web frameworks There is an advantage that services using machine learning can be released to the world as soon as possible.

3. Many reference books and sites!

The final reason is that there are plenty of books and sites that you can use to study machine learning in Python.

Isn't this the most important point for those who are just starting out?

@Carat_yoshizaki, who also runs Kikagaku Online Since it introduces recommended reference books for machine learning beginners, Please also refer to this.

[For machine learning beginners] 30 items to suppress first and 20 recommended reference books

in conclusion

So far, I've introduced three reasons why machine learning learners should use Python.

Kikagaku Online will also introduce machine learning methods using Python, so Let's study together!

Kikagaku Online

** Kikagaku Online ** delivers articles for introductory machine learning.

We handle a wide range of articles, from basic course articles for those who want to learn machine learning, artificial intelligence, and deep learning, to business introduction examples using machine learning.

Recommended Posts

Three Reasons Why Machine Learning Learners Should Use Python
Use machine learning APIs A3RT from Python
Why Python is chosen for machine learning
[Python / Machine Learning] Why Deep Learning # 1 Perceptron Neural Network
Machine learning with Python! Preparation
Python Machine Learning Programming> Keywords
How to use machine learning for work? 03_Python coding procedure
Why you should use Pandas apply ()
Machine learning with python (1) Overall classification
Machine learning summary by Python beginners
<For beginners> python library <For machine learning>
Python: Preprocessing in Machine Learning: Overview
"Scraping & machine learning with Python" Learning memo
Why you should use urlopen instead of urlretrieve to download Python files
Python & Machine Learning Study Memo: Environment Preparation
scikit-learn How to use summary (machine learning)
Notes on PyQ machine learning python grammar
Amplify images for machine learning with python
Machine learning with python (2) Simple regression analysis
I installed Python 3.5.1 to study machine learning
[python] Frequently used techniques in machine learning
"Python Machine Learning Programming" Summary Note (Jupyter)
Python: Preprocessing in machine learning: Data acquisition
[Shakyo] Encounter with Python for machine learning
[Python] First data analysis / machine learning (Kaggle)
[Python] When an amateur starts machine learning
[Python] Web application design for machine learning
Python 3 multi-process Pool methods should use imap_unordered
An introduction to Python for machine learning
[Python] Saving learning results (models) in machine learning
Python: Preprocessing in machine learning: Data conversion
Python & Machine Learning Study Memo ③: Neural Network
Python & Machine Learning Study Memo ④: Machine Learning by Backpropagation
Python & Machine Learning Study Memo ⑥: Number Recognition
Build AI / machine learning environment with Python
Machine learning
python learning
Machine learning starting with Python Personal memorandum Part2
Python & Machine Learning Study Memo ⑤: Classification of irises
Machine learning starting with Python Personal memorandum Part1
Upgrade the Azure Machine Learning SDK for Python
Python & Machine Learning Study Memo ②: Introduction of Library
[Python] Data analysis, machine learning practice (Kaggle) -Data preprocessing-
[Note] Python, when starting machine learning / deep learning [Links]
[Python] Collect images with Icrawler for machine learning [1000 images]
Get a glimpse of machine learning in Python
I started machine learning with Python Data preprocessing
Python & Machine Learning Study Memo ⑦: Stock Price Forecast
Build a Python machine learning environment with a container
You should know if you use Python! 10 useful libraries