About mlwebapp
Learn AI by putting it into practice.
mlwebapp is a personal website about artificial intelligence. It has two goals: understand machine learning and deep learning, then build web applications that use model outputs. The first lessons explain the concepts with no prerequisites. Practical lessons use executed code and data you can inspect.
Six topics to learn and build
Choose a topic to find its content, or follow the step-by-step learning path if you are starting out. Each topic distinguishes available lessons from those in preparation.
Understanding AI
Concepts, tasks, how models work and their limits. Understand what a model does and choose a useful question.
2 published articles
Python for machine learning
Language, environment, libraries and project code. Write, read and reuse Python code.
4 published articles
Data, statistics and visualisation
Data quality, exploration, preparation and charts. Explain the data and prepare it correctly.
Lessons in this category are in preparation.
Machine learning
Models, evaluation and interpretation. Compare results and justify the choice of a model.
Lessons in this category are in preparation.
Web applications with models
Streamlit, APIs, interfaces and model use. Build an application that uses a prediction.
Lessons in this category are in preparation.
Deep learning
Neural networks, training and comparison. Explore models further after learning the foundations.
Lessons in this category are in preparation.
A practical method
Understand through experiments
- One concept at a time, with the terms you need to understand it.
- Examples executed before publication, presented in Jupyter notebooks.
- Exercises with solutions to help you practise.
- A continuous project that connects the lessons.
AI explained with care
Show the limitations too
Models make mistakes, and results depend on the data chosen. The lessons explain how to avoid data leakage, why association does not establish causation, and why performance is meaningful only when measured on data reserved for evaluation.
Official references, such as the Python documentation, remain useful for looking up a specific function.
The publisher
Who publishes mlwebapp?
The website is published by eljihaoui. If an example causes a problem or you notice an error, include the page in your message so the lesson can be corrected.
The legal notice identifies the publisher and hosting provider. The privacy policy describes how data related to the website is used.
Where should you start?
The first lesson introduces AI terminology with no prerequisites. The curriculum then explains the next stages.