Original title: Seven Claws Source Code: Why is Python the best language for machine learning?
AI is popular, so is Python, and there is a lot of evidence to support both. Interestingly, the growth of AI and Python is in direct proportion. how? This is because Python is widely regarded as the best programming language for artificial intelligence and machine learning, which are the most critical and popular technologies for enterprises.
A survey report released by Forbes in 2017 showed that from 2013 to 2017, machine learning (ML) patents grew at a compound annual growth rate of 34%. Today, machine learning has become an indispensable part of global business. It dominates the market and provides important data for enterprises. These data shape marketing strategies and greatly affect customers' purchase behavior.
ML studies algorithms used to analyze data and parse it into meaningful information. There is no doubt that ML coding needs experts in programming languages and programmers. In 2018, Github published an article in which it was reported that Python ranked first as a top machine learning language.
Although it is well known that Python is a developer's preference for AI, many people still forget the reason. Here, let's take a look at the main reasons why Python is absolutely popular with ML developers.
The main reasons why machine learning developers like Python best
1. Learning curve
Although Java, JavaScript, C++and other long-standing languages can compete with it, Python has entered the competition and become the winner. One of the biggest reasons for this is its simple learning curve. This general-purpose and dynamically typed programming language has an easy to read syntax. This means that even novices can use it.
When developers use a coding language with a simple learning curve, they can easily try the solution instead of spending energy and time learning every technical detail accurately.
2. Portability
Python is loved by developers because of its portability and extensibility. Portability means that programmers can use the same code on different machines. For example, if you write Python code for Windows, you can execute the same code on a Mac without having to write a new program from scratch.
This is also possible because Python has cross platform support. MacOS, Solaris, and Linux also support object-oriented programming languages, as well as Windows. Since programmers do not need to write different programs for different platforms, this means that it saves a lot of time and increases the usability of programmers.
3. Scalability
Extensible programming language means that it can be extended and integrated with other programming languages to make it more powerful and purposeful. Extensibility is another important reason why developers prefer Python over other languages. Its extensibility allows programmers to integrate it with other popular languages, such as Java, C++, and components of. NET. Developers can use its scalability to make the algorithm more efficient.
4. A large number of libraries and frameworks
Python's extensive set of frameworks and libraries is another compelling reason to classify it as the language most suitable for ML. The implementation of artificial intelligence algorithm is a thorny thing. If the resources are not suitable, it will consume a lot of time. The right infrastructure, such as the test environment, coding framework, functional modules and libraries, provides the necessary structure to make it easier, and Python has everything.
Some of the most useful libraries in its extremely rich technology ecosystem are listed below.
-SciPy - for scientific and technical computing
-TensorFlow - a Python based library that focuses on deep neural networks
-Keras - a library that provides Python interfaces for artificial neural networks
-Scikit - a powerful Python machine learning library
-NumPy - a library supporting multidimensional arrays and a large number of mathematical functions (such as gradient lifting, regression, linear algebra, etc.), which can operate on arrays
5. Visualization options
Visualization is the basic component of data, and data is the pillar of AI and ML. The presentation of data needs to be visualized, because this is the way that the non-technical public can draw conclusions from all these variables. Fortunately, Python provides its users with some very good visualization options.
The Python library has once again saved programmers, because the language provides some feature rich libraries as classic visualization tools. With the help of these libraries, developers can make charts, graphs, plots and histograms for better understanding. Some Python libraries that are good at these tasks are:
-GGPlot - Python's data visualization library, which can help create error charts, pie charts, bar charts, etc., and use advanced APIs. Programmers can also combine various types of visualization components in a single visualization.
-Matplotlib - It is the most widely used Python library for data visualization and 2D drawing, with a highly interactive environment. It provides programmers with a series of tools to create data visualization, including scatter plot, stem plot and power spectrum.
-Seaborn - Matplotlib based visualization library, integrated with Pandas data structure. It is also useful for creating infographs and provides tools for selecting palettes that help reveal data patterns.
6. Strong community support
The power of the community is best reflected in the development of WordPress. Countless themes, libraries, frameworks, APIs and modules - there is almost nothing that cannot be found in WordPress, let alone the great help to overcome any technical difficulties. Python also has a great community, which supports the language and its users, and helps programmers easily use their Python development services.
Take it away
We now know that Python has established itself as the best programming language for AI and ML, and we now know that there are some very good reasons to support its victory. Although the language is easy to learn and use, it certainly needs experts to make full use of it. Therefore, if you want to have an unparalleled ML algorithm in your application, the most sensible choice is to rent Python development services from a reliable partner.
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