Machine Learning with ML.Net for Absolute Beginners

🚀 Course Title: Machine Learning with ML.Net for Absolute Beginners

🎓 Course Headline: Dive into the World of Machine Learning with .NET Skills using ML.Net 1.5.0-preview2!

Introduction:

Machine Learning is a transformative approach to enabling computers to learn from experience and make predictions based on that experience. It's a field within computer science that has the potential to revolutionize industries, enhance user experiences, and provide insights from data at an unprecedented scale. 🧠✨

Getting Started with ML.Net:

ML.Net is Microsoft's open-source machine learning framework that allows developers with .NET skills to add machine learning capabilities directly within their applications. It's free, open-source, and cross-platform, making it accessible for a wide range of applications on both dotnet core and the dotnet framework.

Course Outline:

• Introduction to Machine Learning: Understand the fundamentals of ML and how it differs from Deep Learning and Artificial Intelligence.
• Understanding ML.Net: Get acquainted with the structure of the ML.Net SDK and what it offers.
• Building Your First Model: Start by creating a regression model and learning how to perform predictions with it.
• Model Evaluation: Master the techniques for evaluating your models and cross-validating them with data.
• Data Handling: Learn how to load, filter, and prepare data from various sources like files, databases, and binary streams.
• Saving and Loading Models: Discover how to save your created models and load them for further operations.
• Binary Classification: Explore binary classification and how to use different trainers to build models that can classify data into two categories.
• Sentiment Analysis: Perform sentiment analysis on text data to understand user sentiments.
• Multiclass Classification: Dive into multiclass classification and learn how to predict multiple classes with ease.
• Computer Vision with TensorFlow Models: Learn how to use ML.Net for computer vision tasks, identifying objects within images.
• Exploring Other Trainers: Get hands-on experience with anomaly detection, ranking, forecasting, clustering, and recommendation algorithms.
• Data Transformation: Master the art of transforming various types of data including Text, Conversion, Categorical, TimeSeries, etc., for better model performance.
• Automated Machine Learning (AutoML): Use ModelBuilder UI and CLI to automate the process of selecting the best model for your dataset.
• ONNX Integration: Understand ONNX (Open Neural Network Exchange) and how to create and use ONNX models within ML.Net applications.
• Real-world Applications: See how you can deploy models within ASP.NET Core applications to perform predictions in real-time.

Why Take This Course? This course is designed for absolute beginners, with no prior knowledge of Machine Learning or ML.Net required. By the end of this course, you'll be equipped to build your own machine learning models and integrate them into .NET applications, all leveraging the power of ML.Net. 🏗️🚀

Join us on this exciting journey to master Machine Learning with ML.Net and take your .NET skills to the next level! 🌟✨