When people are interested in getting a grasp on machine learning, getting involved in a Python project is an excellent way to do it. Then, it’s possible to take a hands-on approach to skill development.
Since everything mentioned here is open-source options, they’re great for helping learners gain visibility into the back end of the code and not have to invest in expensive software.
Learn Object Detection in Images Using PyTorch and the YOLO Algorithm
PyTorch is a type of open-source software based in Python often used in machine-learning projects. People can use it to detect objects in images with help from the YOLO algorithm that’s sometimes referred to by its full name You Only Look Once. One of the positive factors of this project is that it works with only nine lines of code.
As such, machine-learning students who try it out shouldn’t feel too overwhelmed when getting started and working through it.
Grasp the Basics of Machine Learning With a SciPy Project as a Starting Point
SciPy is another open-source platform that runs on Python, and it offers a wealth of opportunities for machine learning. However, when people are just starting, it can seem daunting to assess the difficulty level of each project as a whole without getting walk-through instructions of each step. This beginner-level project is an excellent place to explore machine learning’s possibilities.
It gets people accustomed to working with data in various ways, including using machine learning to predict species of flowers based on their measurements.
Make a Neural Network With Keras and Python
This project involves using Keras with Python. This is an open source machine learning library containing neural networks, and it runs on top of several other software titles also used in machine learning, such as PlaidML and TensorFlow. People who do this project don’t need to know a lot of code, but they’ll start to learn how neural networks function.
It gives a detailed tutorial for creating a neural network. After going through it, people should feel substantially more confident about realizing the potential of another Python machine-learning project on their own.
Switch the Gender of a Person in a Portrait
After people get engrossed in this machine-learning project, they’ll see how quickly it can distort the faces of people in photos. It’s easy to see how such a technique could have unsettling implications, such as if a photographer knowingly changes a picture of a celebrity without permission. However, at this level, people can get involved in a fun machine-learning project that alters the masculinity or femininity of a person’s photo in a believable way.
As a word of caution, a GPU for training the models is only optional for this project. However, coverage of this project on Analytics Vidhya warned that it takes about two hours to prepare each model if people don’t use a GPU.
Detect and Track Images Using PyTorch
This is another Python machine-learning project that uses PyTorch, and it’s an extension of the earlier option mentioned here that used YOLO for image recognition. In this case, people learn to use a pretrained classifier to recognize multiple objects in an image, and then track them across a video in a later step.
The person who wrote the tutorial mentioned that once people know enough about how the YOLO algorithm works, they can go beyond this project and train their own images. They can achieve similar results while becoming even more involved in how machine learning works.
It’s Time to Take on Some Projects
This assortment of Python machine-learning projects shows it’s not difficult for people who are just getting started to dive in and see what they can do. Since the tutorials mentioned here give a breakdown of each step, learners can follow them at their own pace and enjoy the process of expanding their skills in meaningful ways.