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src/content/docs/product-case-study/machine-learning.md

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+# Machine Learning Case Study
+
+*Student: Terese Wick
+*Course: 
+
+# Summary
+This is a raport that tells about how machine learning (ML) has evolved from the first models in the 1940s, to the practical use it has today in web development. The report shows how ML can be used as a tool for developers (testing and coding) and as a feature in applications (e.g. chatbots). The goal is to provide a better understanding of how ML can contribute to efficiency in the development process itself and a better en product.
+
+# Introduction
+ML is a sub-branch of arttificial intelligence (AI). Its focus is on allowing systems to learn from data and improve performance without being explicitly programmed. While AI is about machines that can mimic human intelligence, ML is about algorithms and models that learn from experience.
+
+# Brief history
+In the 1940s, the desire to build machines that learn from data began.
+- 1943 McCulloch an Pitts presented a mathematical model of artificial neurons.
+- 1958 Rosenblatt developed an early attempt at pattern recognition using machinlearning.
+1970-90s development was slowed by limited computing power. However, with the advent of faster hardware and larger datasets in the 2000s, more complex models became possible.
+
+## Machin learning in development
+
+# ML as a tool
+
+Machine learning can be effective in the development process in several ways.
+- AI powered testing: Simulate user behavior, detect hidden errors.
+- Visual regression testing: Can detect changes in design between diffrent versions.
+- AI-assisted design: Create sketches, content (text,images).
+- AI pair programming: Github Copilot is a tool that can, for example, make code suggestion or fix errors.
+
+# ML as functionally
+- Chatboter: NLP-based systems. Provide language-based customer support.
+- Recommenddation system: Used by, for example, Netflix.
+- Media recognition: For example, tagging images, video and audio.
+
+# Summary
+Machine learning has evolved from an idea to a tool in web development.
+- Efficient developmwnt process.
+- Better code quality and productivity.
+- Give web applications intelligent functions.
+
+# Sources and further reading
+https://developers.google.com/machine-learning
+https://cloud.google.com/product/ai
+https://aws.amazon.com/machine-learning/