Ongoing support and development is continuing for Python 3. If you’re just starting with Python, you should use Python 3. Official support for Python 2 will end in the beginning of 2020. Python 2 is an older version that’s still used fairly often, and is still installed as the default version of Python in some current operating systems. ![]() ![]() Whether to use Python 2 or Python 3 is a common source of confusion for people new to the language. Once we get to machine learning libraries, datasets, and visualizations, you’ll find them helpful. Package management systems including apt-get, rpm, homebrew, and othersĪnother choice is the Jupyter Notebooks and JupyterLabs interactive development tools.Ī third choice - and the one we recommend and will use for these Python AI/ML articles - Anaconda, a comprehensive software platform designed specifically for statistics, data science, and AI/ML projects.Īnaconda includes JupyterLab, the web-based IDE mentioned earlier, along with many of the other tools, libraries, and sample data sources you're likely to need when learning about AI.For systems that do not have Python, you can get the installer from: Python is installed by default on Mac OS and some Linux distributions. The answer is: it depends on your system and programming environment. The first question developers usually ask is: where do I get Python? How familiar language concepts like syntax and variables work in Python.The difference between Python 2 and Python 3. ![]() This article will introduce you to important Python basics including: Python is the most commonly used language for most AI and ML application development - even for prototyping and optimizing models for those IoT and hardware-accelerated applications.įor developers coming to Python from other languages such as C#, Java, and even JavaScript, this article introduces you to key elements of Python’s unique syntax, such as loops, and how they differ from what you might know.Īdditional articles in this series will explore how to work with numerous Python libraries available for AI and ML developers such as OpenCV, Natural Language Toolkit (NLTK), Keras, and TensorFlow. Most of the time, C/C++ is used in specialized applications such as with embedded Internet of Things (IoT) and highly optimized, hardware-specific neural network libraries. When developers begin working with artificial intelligence (AI) and machine learning (ML) software, the programming languages they're most likely to encounter today are Python and C/C++.
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