Made-With-ML
ML development guide
Teaches machine learning fundamentals and software engineering practices for building production-ready ML applications
Learn how to design, develop, deploy and iterate on production-grade ML applications.
38k stars
1k watching
6k forks
Language: Jupyter Notebook
last commit: about 1 year ago
Linked from 1 awesome list
data-engineeringdata-qualitydata-sciencedeep-learningdistributed-mldistributed-trainingllmsmachine-learningmlopsnatural-language-processingpythonpytorchray
Related projects:
| Repository | Description | Stars |
|---|---|---|
| | A structured study plan to help software developers learn machine learning and become a machine learning engineer | 28,216 |
| | A cross-platform machine learning framework for .NET that enables developers to build, train, and deploy models without prior expertise in ML. | 9,071 |
| | A collection of samples and examples demonstrating the usage of ML.NET for machine learning tasks in .NET applications. | 4,508 |
| | A structured curriculum teaching classic machine learning techniques using Python and Scikit-learn, with a focus on practical projects and hands-on exercises. | 70,139 |
| | A resource guide covering the four main steps of designing a machine learning system: project setup, data pipeline, modeling, and serving. | 9,227 |
| | A platform for managing machine learning projects from inception to deployment | 19,021 |
| | Teaches practical aspects of productionizing ML services | 11,227 |
| | A guide to building production-ready deep learning systems for real-world applications | 4,371 |
| | Practices implementing popular machine learning algorithms from scratch to gain a deeper understanding of their mathematics | 23,191 |
| | Automates machine learning workflows and generates reports on every pull request. | 4,046 |
| | Provides implementations of fundamental machine learning models and algorithms from scratch in Python | 24,092 |
| | Makes machine learning algorithms accessible to web developers | 6,510 |
| | An explanation of key concepts and advancements in the field of Machine Learning | 7,352 |
| | Automates conversion of machine learning code into production-ready microservices with web API and GUI. | 3,116 |
| | An all-in-one web-based IDE for machine learning and data science | 3,446 |