
Explore the definition and applications of machine learning, cover supervised and unsupervised learning, and implement PHP algorithms to build models that classify data, persist data, and assess accuracy.
Introduce machine learning in PHP, showing data-driven learning without explicit programming, and compare supervised, unsupervised, semi-, self-, and reinforcement learning with common algorithms and evaluation metrics.
Decide whether to write PHP machine learning algorithms or use libraries like PHP ML and Rubik's ML, then require via composer and vendor to access classification, clustering, and regression tools.
Build your first PHP machine learning model by loading the insurance csv with PHP ML, preprocessing and splitting data, training a linear regression with least squares, and predicting unseen values.
Explore supervised learning with classification, using k nearest neighbors to map discrete categories like iris species and wine quality, and compare accuracy against regression in PHP.
Master model persistency in PHP by training once, saving the classifier to a file with a model manager, and restoring it later to make predictions without retraining, preserving accuracy.
PHP offers speed, modernity, and ease of learning for machine learning, but has fewer libraries and requires more efficient algorithms for large-scale, multimodal data.
WHY Machine Learning
Machine learning is a rapidly growing field that is changing the way technology and solving complex problems.
Machine learning is widely used in industries such as healthcare, finance, marketing, and self-driving cars to automate processes, improve decision making, and provide personalized experiences to customers.
The amount of data generated by society is continually growing, further increasing the demand for skilled machine learning practitioners.
Learning machine learning provides valuable skills for a career in technology and data science.
The demand for machine learning talent is growing at a rapid pace, with the number of job postings for machine learning roles increasing by over 75% in the past 5 years.
WHY PHP
PHP is used in more than 70 percent of the websites across the Internet. That’s HUGE!
PHP is more alive than ever! It’s simple yet very powerful. It’s secure. It’s scalable.It’s very easy to learn.
Just to get an idea of how powerful PHP is, Websites like Facebook, Wikipedia, Slack, MailChimp, Flickr, SourceForge, Tumblr, Etsy and Yahoo have PHP as their core.
oh and not to forget, the biggest blogging system on the web (WordPress), is powered by PHP.
enough teasing let’s get started with Machine Learning in PHP.
In this course:
You Will Learn how to implement some of the most common machine learning algorithms in PHP
You will Learn about the some of the common algorithms like classification, regression, clustering
You will learn about Supervised and Unsupervised learning
You will NOT learn the details and mathmatics of each algorithm. Our focus is mainly on implementing them in PHP
You will Learn about the steps to build a machine learning model
You will Learn how to divide your data to training set and test set
You will Learn how to train your machine learning model
You will Learn how to make prdictions
You will learn about the persistency of your model
and a lot more
Prior Knowledge
Basic knowledge of Machine learning is a plus because we are not going though the details of each algorithm and our main focus is on the implementation in PHP
Basic Knowledge about PHP is a plus.
This Course is for:
PHP Developers who want to start their journey in Machine Learning
Developers who are familiar with Machine Learning and want to learn how to implement them in PHP
Curious to learn about Machine Learning
If this is you, then what are you waiting for?! Let’s get Started