The First 3 Tools to Learn as an AI Developer

The First 3 Tools to Learn as an AI Developer

Want to get into developing AI-powered apps? Do you already have the background as a traditional software developer? Let me give you a quick roadmap of 3 surprisingly simple tools you can learn which will set you up for success on your journey into building AI-powered apps.

Skill #1: Python

Python is not the fastest language. Some would say it's not the most beautiful. But it has the most momentum behind it for developing AI capabilities.

Get started today with a free course like Coursera's "Python for Everybody": https://www.coursera.org/specializations/python

Skill #2: Jupyter Notebooks

Most AI content is explained using a technology called Jupyter notebooks. You've probably heard of them. They allow you to get instant feedback on commands you run without having to get full applications running.

Google Colabs is a great free resource for online Jupyter notebooks: https://colab.google/

Skill #3: Hugging Face

If you've used Github or Docker, you know how helpful it is to have a community hub for sharing stuff. Github is the hub for code. Docker for container images. Hugging Face is the de facto hub for Machine Learning and AI.

It has 3 main components:

  1. Models
    Allows you to build on top of open-source and closed-source AI models in standard way.

  2. Datasets
    A collection of data sets you can use to train your own custom models. Especially helpful if you want to immediately get started practicing with a new technology and don't want to spend days cleaning your own data sets in preparation.

  3. Spaces
    A place to share rudimentary front ends that expose your models in a way that anyone can test them out and interact with them.

Hugging Face also provides a serverless inference endpoint that allows you to hit models in the cloud without bogging down your local machine.

https://huggingface.co/

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