Welcome to the AI & ML for PHP Channel!
This channel is created for developers, enthusiasts, and anyone interested in learning artificial intelligence and machine learning with PHP. Here, we will explore key AI and ML concepts, share practical examples, useful libraries (PHP-ML, Rubix ML), and discuss how to apply machine learning in PHP projects.
What to expect?
• Clear explanations of complex topics
• Step-by-step breakdowns of ML algorithms with working examples
• Guides on libraries and tools
• Discussions on current AI and PHP trends
Subscribe, join the discussions, and level up your skills!
What topics interest you the most? Share your thoughts in the comments, and we’ll cover them in future posts!
#AI #ML #PHP #MachineLearning #ArtificialIntelligence #PHPML #RubixML
This channel is created for developers, enthusiasts, and anyone interested in learning artificial intelligence and machine learning with PHP. Here, we will explore key AI and ML concepts, share practical examples, useful libraries (PHP-ML, Rubix ML), and discuss how to apply machine learning in PHP projects.
What to expect?
• Clear explanations of complex topics
• Step-by-step breakdowns of ML algorithms with working examples
• Guides on libraries and tools
• Discussions on current AI and PHP trends
Subscribe, join the discussions, and level up your skills!
What topics interest you the most? Share your thoughts in the comments, and we’ll cover them in future posts!
#AI #ML #PHP #MachineLearning #ArtificialIntelligence #PHPML #RubixML
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PHP has been a leader in web development for decades, but its potential for artificial intelligence remains unexplored.
I think now is the time to start widely use PHP language with AI and Machine Learning, as there is a great demand for it on the internet and... here we go!
Let's start from understanding what exactly AI is and it's structure.
I think now is the time to start widely use PHP language with AI and Machine Learning, as there is a great demand for it on the internet and... here we go!
Let's start from understanding what exactly AI is and it's structure.
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When you speak about AI you have to take in account, that AI consists of various specialized fields, each focusing on different aspects of creating intelligent machines.
Here are some of the key areas of AI:
🔹 Machine Learning (ML)
Algorithms that enable machines to learn from data and make predictions. Used in recommendation systems, image recognition, and fraud detection.
🔹 Neural Networks & Deep Learning (DL)
Models inspired by the human brain that can analyze complex patterns. Essential for image and speech recognition, as well as autonomous systems.
🔹 Natural Language Processing (NLP)
Teaches machines to understand, interpret, and generate human language. Powers chatbots, translation tools, and voice assistants.
🔹 Computer Vision
Enables machines to interpret and understand visual data. Used in facial recognition, autonomous vehicles, and medical imaging.
🔹 Robotics
Combines AI with engineering to create robots that can navigate, perceive, and interact with their environment. Applied in manufacturing, healthcare, and space exploration.
🔹 Cognitive Computing
Simulates human thought processes, allowing machines to learn, reason, and understand language. Used in pattern recognition, data mining, and intelligent assistants.
🔹 Expert Systems
AI-driven systems that replicate human decision-making using rule-based knowledge. Useful in medical diagnosis, finance, and technical troubleshooting.
🔹 AI Ethics & Safety
Focuses on the ethical considerations and risks of AI, including bias, transparency, and the societal impact of automation.
So... as you understand, AI is not only GPT chat, it is much more ))
Here are some of the key areas of AI:
🔹 Machine Learning (ML)
Algorithms that enable machines to learn from data and make predictions. Used in recommendation systems, image recognition, and fraud detection.
🔹 Neural Networks & Deep Learning (DL)
Models inspired by the human brain that can analyze complex patterns. Essential for image and speech recognition, as well as autonomous systems.
🔹 Natural Language Processing (NLP)
Teaches machines to understand, interpret, and generate human language. Powers chatbots, translation tools, and voice assistants.
🔹 Computer Vision
Enables machines to interpret and understand visual data. Used in facial recognition, autonomous vehicles, and medical imaging.
🔹 Robotics
Combines AI with engineering to create robots that can navigate, perceive, and interact with their environment. Applied in manufacturing, healthcare, and space exploration.
🔹 Cognitive Computing
Simulates human thought processes, allowing machines to learn, reason, and understand language. Used in pattern recognition, data mining, and intelligent assistants.
🔹 Expert Systems
AI-driven systems that replicate human decision-making using rule-based knowledge. Useful in medical diagnosis, finance, and technical troubleshooting.
🔹 AI Ethics & Safety
Focuses on the ethical considerations and risks of AI, including bias, transparency, and the societal impact of automation.
So... as you understand, AI is not only GPT chat, it is much more ))
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I believe we are now at the beginning of a new era — the Era of AI Agents! Just imagine, 30-40 years ago, we started with functional programming, then for many years, we used OOP, DDD, BDD, and many other cool and funny approaches. Now, a new programming paradigm comes — LLM AI Agents Driven Design.
Check out this introduction to LLM AI PHP Agents and think about the future of AI-driven development!
Check out this introduction to LLM AI PHP Agents and think about the future of AI-driven development!
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It's important to know (for better understanding), that AI can be categorized based on what it can do and how it works. Let’s break it down!
🧠 Type 1: Based on Capabilities
1. Weak AI (Narrow AI) – Focuses on a specific task, like Siri, self-driving cars, or image recognition (already among us).
2. General AI (Strong AI) – Would think and learn like a human, but we haven’t built it yet (still not).
3. Super AI – Smarter than humans in every way, but purely theoretical for now (e.g., Skynet - still not, 10xG-d!).
⚙️ Type 2: Based on Functionality
1. Reactive Machines – Only respond to situations based on programming (e.g., IBM Deep Blue, AlphaGo, iRobot, etc).
2. Limited Memory AI – Uses past data for short-term decision-making (e.g., self-driving cars).
3. Theory of Mind AI – Would understand human emotions and interact socially (still in development).
4. Self-Awareness AI – Would have its own consciousness and emotions (a future possibility).
The most important that AI is constantly evolving (faster than we are)...
🧠 Type 1: Based on Capabilities
1. Weak AI (Narrow AI) – Focuses on a specific task, like Siri, self-driving cars, or image recognition (already among us).
2. General AI (Strong AI) – Would think and learn like a human, but we haven’t built it yet (still not).
3. Super AI – Smarter than humans in every way, but purely theoretical for now (e.g., Skynet - still not, 10xG-d!).
⚙️ Type 2: Based on Functionality
1. Reactive Machines – Only respond to situations based on programming (e.g., IBM Deep Blue, AlphaGo, iRobot, etc).
2. Limited Memory AI – Uses past data for short-term decision-making (e.g., self-driving cars).
3. Theory of Mind AI – Would understand human emotions and interact socially (still in development).
4. Self-Awareness AI – Would have its own consciousness and emotions (a future possibility).
The most important that AI is constantly evolving (faster than we are)...
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Machine Learning: How Computers Learn Like Humans!
Did you ever wonder how Netflix recommends shows you love or how Siri understands your voice? That’s Machine Learning in action! It’s a subset of AI that helps computers learn from data and make smart decisions — just like you and me do!
How Machine Learning Works
- Collect Data: You gather a set of data related to the problem you want to solve.
- Train the Model: The machine learning algorithm uses this data to learn patterns. During training, the model adjusts its internal parameters to improve its accuracy.
- Test the Model: After training you test the model on new data to see if it can make good predictions.
- Make Predictions: Once trained and tested, the model can predict outcomes on new, unseen data.
Unlike traditional programming, where every rule is manually coded, Machine Learning adapts and improves over time!
Next time we'll talk about which kind of problems can be better solved with machine learning and present popular PHP libraries for ML.
Did you ever wonder how Netflix recommends shows you love or how Siri understands your voice? That’s Machine Learning in action! It’s a subset of AI that helps computers learn from data and make smart decisions — just like you and me do!
How Machine Learning Works
- Collect Data: You gather a set of data related to the problem you want to solve.
- Train the Model: The machine learning algorithm uses this data to learn patterns. During training, the model adjusts its internal parameters to improve its accuracy.
- Test the Model: After training you test the model on new data to see if it can make good predictions.
- Make Predictions: Once trained and tested, the model can predict outcomes on new, unseen data.
Unlike traditional programming, where every rule is manually coded, Machine Learning adapts and improves over time!
Next time we'll talk about which kind of problems can be better solved with machine learning and present popular PHP libraries for ML.
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PHP is not Python, but that doesn't mean it can't be used for machine learning and scientific computing!
There are many legacy PHP libraries that were started 7-10 years ago, were abandoned most likely due to Python and are no longer supported, so I have listed only the most current and actively developed ones (thanks to the loyal PHP community).
Below you may find some of the most powerful libraries available for PHP.
Machine Learning Libraries
🔹 Rubix ML – One of the most powerful ML libraries for PHP.
- Supports more than 40+ supervised and unsupervised algorithms (neural networks, decision trees, clustering).
- Includes data transformation, pipelines, and model evaluation tools. Official website: https://rubixml.com
Mathematical Libraries (for Scientific Computing)
🔹 NumPower – A PHP alternative to NumPy!
- High-performance numerical computing with GPU acceleration.
- Supports multi-dimensional arrays and linear algebra operations.
Official website: https://numpower.org
🔹 MathPHP – A modern mathematics library for PHP.
- Pure PHP with no external dependencies.
- Offers a wide range of mathematical functions.
Official website: https://github.com/markrogoyski/math-php
🔹 RubixML/Tensor – A high-performance tensor and matrix operations library for PHP.
- Optimized for speed using PHP’s native extensions.
- Provides essential linear algebra tools for scientific computing and ML.
Github: https://github.com/RubixML/Tensor
If you are interested in using RubixML in your projects, you can find many video tutorials on youtube. Here is just one example: https://www.youtube.com/watch?v=zJc_Vju72dg
There are many legacy PHP libraries that were started 7-10 years ago, were abandoned most likely due to Python and are no longer supported, so I have listed only the most current and actively developed ones (thanks to the loyal PHP community).
Below you may find some of the most powerful libraries available for PHP.
Machine Learning Libraries
🔹 Rubix ML – One of the most powerful ML libraries for PHP.
- Supports more than 40+ supervised and unsupervised algorithms (neural networks, decision trees, clustering).
- Includes data transformation, pipelines, and model evaluation tools. Official website: https://rubixml.com
Mathematical Libraries (for Scientific Computing)
🔹 NumPower – A PHP alternative to NumPy!
- High-performance numerical computing with GPU acceleration.
- Supports multi-dimensional arrays and linear algebra operations.
Official website: https://numpower.org
🔹 MathPHP – A modern mathematics library for PHP.
- Pure PHP with no external dependencies.
- Offers a wide range of mathematical functions.
Official website: https://github.com/markrogoyski/math-php
🔹 RubixML/Tensor – A high-performance tensor and matrix operations library for PHP.
- Optimized for speed using PHP’s native extensions.
- Provides essential linear algebra tools for scientific computing and ML.
Github: https://github.com/RubixML/Tensor
If you are interested in using RubixML in your projects, you can find many video tutorials on youtube. Here is just one example: https://www.youtube.com/watch?v=zJc_Vju72dg
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If you want to build a career in AI, ML or Big Data
The world of AI, ML and Big Data is growing every day, and if you want to dive into Data & AI, it's important to choose the right path. It's not so simple to decide: who to become? Let's check which options are available today for your choice:
1. Data Scientist – the AI magician 🧙♂️ who builds machine learning models, analyzes data, and makes predictions. Key skills: Python, statistics, ML, SQL, C.
2. Data Analyst – the data detective 🔍 who digs deep into numbers, creates reports, and finds hidden patterns. Tools of choice: PHP, SQL, Excel, BI systems (Tableau, Power BI), etc.
3. Data Engineer – the data architect 🏗️ who designs and maintains data pipelines and storage. Must-know: Python, SQL, Spark, ETL, databases.
4. ML Engineer – the model optimizer 🚀 who takes machine learning from theory to production. Required skills: PHP, Python, TensorFlow/PyTorch, DevOps, MLOps.
5. AI Enthusiast – the explorer 🌍 who experiments with AI, joins Kaggle competitions, and builds cool projects just for fun. Required skills: PHP, Python, JS, databases. etc.
Which role suits you best?
The world of AI, ML and Big Data is growing every day, and if you want to dive into Data & AI, it's important to choose the right path. It's not so simple to decide: who to become? Let's check which options are available today for your choice:
1. Data Scientist – the AI magician 🧙♂️ who builds machine learning models, analyzes data, and makes predictions. Key skills: Python, statistics, ML, SQL, C.
2. Data Analyst – the data detective 🔍 who digs deep into numbers, creates reports, and finds hidden patterns. Tools of choice: PHP, SQL, Excel, BI systems (Tableau, Power BI), etc.
3. Data Engineer – the data architect 🏗️ who designs and maintains data pipelines and storage. Must-know: Python, SQL, Spark, ETL, databases.
4. ML Engineer – the model optimizer 🚀 who takes machine learning from theory to production. Required skills: PHP, Python, TensorFlow/PyTorch, DevOps, MLOps.
5. AI Enthusiast – the explorer 🌍 who experiments with AI, joins Kaggle competitions, and builds cool projects just for fun. Required skills: PHP, Python, JS, databases. etc.
Which role suits you best?
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What to read?
I'm planning to post here information about books, articles or other interesting materials related to AI or ML. This is the first one. So.. Get it:
Andriy Burkov, The Hundred-Page Language Models Book
https://themlbook.com/
This book provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much about machine learning.
✅ Pros
1. Straight to the Point – The book explains machine learning ideas quickly and clearly without extra details. This makes it great for busy people.
2. Easy for Beginners – It gives a simple introduction to machine learning, so newcomers won’t feel lost.
3. Includes Some Math – It covers important math concepts like probability and algebra, but it doesn’t go too deep.
4. Helpful for Interviews – If you're preparing for a machine learning job interview, this book is a great refresher.
5. Covers Old and New ML Methods – It talks about basic models like decision trees and modern AI like deep learning.
❌ Cons
1. Too Short for Deep Learning – The book moves very fast, so you might need another book for more details.
2. Not Many Code Examples – It explains ML well but doesn’t show much actual coding. If you want hands-on practice, you'll need another resource.
3. Some Prior Knowledge Helps – While it’s good for beginners, a basic understanding of math and ML will make it easier to follow.
🎓 The Verdict
This book is like a pocket-sized AI mentor — super useful, incredibly insightful, and refreshingly brief. But if you're looking for deep, hands-on coding exercises or advanced ML theory, you'll need something else.
Not sure if you're ready to buy it? Read this first: https://themlbook.com/wiki/doku.php
I'm planning to post here information about books, articles or other interesting materials related to AI or ML. This is the first one. So.. Get it:
Andriy Burkov, The Hundred-Page Language Models Book
https://themlbook.com/
This book provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much about machine learning.
✅ Pros
1. Straight to the Point – The book explains machine learning ideas quickly and clearly without extra details. This makes it great for busy people.
2. Easy for Beginners – It gives a simple introduction to machine learning, so newcomers won’t feel lost.
3. Includes Some Math – It covers important math concepts like probability and algebra, but it doesn’t go too deep.
4. Helpful for Interviews – If you're preparing for a machine learning job interview, this book is a great refresher.
5. Covers Old and New ML Methods – It talks about basic models like decision trees and modern AI like deep learning.
❌ Cons
1. Too Short for Deep Learning – The book moves very fast, so you might need another book for more details.
2. Not Many Code Examples – It explains ML well but doesn’t show much actual coding. If you want hands-on practice, you'll need another resource.
3. Some Prior Knowledge Helps – While it’s good for beginners, a basic understanding of math and ML will make it easier to follow.
🎓 The Verdict
This book is like a pocket-sized AI mentor — super useful, incredibly insightful, and refreshingly brief. But if you're looking for deep, hands-on coding exercises or advanced ML theory, you'll need something else.
Not sure if you're ready to buy it? Read this first: https://themlbook.com/wiki/doku.php
Themlbook
The Hundred-Page Machine Learning Book by Andriy Burkov
All you need to know about Machine Learning in a hundred pages.
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News: New Chinese AI Agent
The Chinese have already joined the AI arms race. Hopefully this year we'll see a real breakthrough that will change the rules of the game (and our world along with us).
https://www.youtube.com/watch?v=a_XRAUC4w_E
- or -
https://manus.im/
The Chinese have already joined the AI arms race. Hopefully this year we'll see a real breakthrough that will change the rules of the game (and our world along with us).
https://www.youtube.com/watch?v=a_XRAUC4w_E
- or -
https://manus.im/
YouTube
This New Chinese AI Agent Is Making OpenAI & Google PANIC! (Manus AI Is Scary)
Is China’s new AI agent, Manus AI, about to dethrone OpenAI and Google? This cutting-edge technology is causing a stir in the global AI community, with its advanced capabilities and potential to outperform established giants. But what makes Manus AI so powerful…
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AI-Powered PHP Agents in Action!
If you’re a PHP developer looking to add AI to your projects, the LLM Agents PHP SDK makes it super easy. You can build smart agents that automate tasks, analyze data, and interact with external tools—all with minimal effort.
Here are two cool real examples, see live demo with code example:
🔹 Site Status Checker – Monitors website uptime and performance, instantly notifying you of any issues.
https://aiwithphp.org/examples/ai-agents/llm-agents/site-status-checker-agent-run
🔹 Sales Analysis Agent – Analyzes sales data, spots trends, and helps businesses make better decisions.
https://aiwithphp.org/examples/ai-agents/llm-agents/sales-analysis-agent-run
P.S. The result is cached, so if you want to install this code examples on your server, you should use your own OpenAI key.
If you’re a PHP developer looking to add AI to your projects, the LLM Agents PHP SDK makes it super easy. You can build smart agents that automate tasks, analyze data, and interact with external tools—all with minimal effort.
Here are two cool real examples, see live demo with code example:
🔹 Site Status Checker – Monitors website uptime and performance, instantly notifying you of any issues.
https://aiwithphp.org/examples/ai-agents/llm-agents/site-status-checker-agent-run
🔹 Sales Analysis Agent – Analyzes sales data, spots trends, and helps businesses make better decisions.
https://aiwithphp.org/examples/ai-agents/llm-agents/sales-analysis-agent-run
P.S. The result is cached, so if you want to install this code examples on your server, you should use your own OpenAI key.
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