Learn how to develop, deploy and iterate on production-grade ML applications.
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In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
Translated📚 Building large models from scratch
💿 Free software that works great, and also happens to be open-source Python.
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
- csharp
- java
- javascript
- mcp
From the basics to slightly more interesting applications of Tensorflow
Open-source demos hosted on Dash Gallery
- plotly-dash
- dash
- plotly
ChatGPT Python Applications integrated with third party libraries and modules
How to create a Cartoonizer Android app with TensorFlow Lite models.
- tensorflow-lite
- tflite
- computer-vision
- gans
Code repository for The Automation Ahead series, showcasing practical examples for GenAI-driven automation in investments. Each installment dives into specific tools, techniques, and use cases to help professionals assess and apply GenAI effectively.
- data-science
- deep-learning
- finance
- financial-data
Sample code for Core ML using ResNet50 provided by Apple and a custom model generated by coremltools.
- ios
- coreml
- coreml-framework
- swift
A coding exercise: let's convert dirty machine learning code into clean code using a Pipeline - which is the Pipe and Filter Design Pattern applied to Machine Learning.