 Made-With-ML
 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 |