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cst438 - week 4

     One of the things that I found interesting from 'Software engineering at Google' was the distinction between programming and software engineering. Before taking this class and reading the text, I viewed software engineering as just an advanced form of designing and integrating large systems. While I understood that practices like code reviews, version control, and project planning were important, I thought of them more as supporting tools rather than a defining part of engineering itself.     It makes a lot of sense now that software engineering encompasses much more than writing code or designing architecture. The processes that guide development like code reviews, version control, project organization, documentation, and team collaboration are what allow software to be developed reliably by many people over long periods of time. These noncoding aspects are what separate software engineering from simply programming. I think this shift in perspective i...
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cst438 - week 3

     One of the biggest advantages of using git for source code management is that it provides a complete history of a project. If a new feature or bug fix accidentally breaks the program its easy to look back through previous commits and return to a working state. Git also makes collaboration much easier by allowing multiple developers to work on different features at the same time without constantly worrying about keeping every file perfectly synchronized. Branches allow developers to experiment independently before integrating their work into the main project.      Though git doesn't solve every problem that someone might run into when multiple developers are working on the same project. Merge conflicts are an most obvious issue, needing developers to manually decide how conflicting changes should be combined. Additionally, even when Git merges code automatically, its unable to determine whether the merged code makes sense logically. Two developers may m...
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cst438 - week 2

     This week we focused on using React alongside Spring Boot to build a full stack web application and learned how the front end communicates with the back end. I really enjoyed this topic because, while previous classes had covered front end or back end development separately, this was one of the first times I got to see how the two actually work together. It was exciting to see how data is passed between the client and server, stored in a database, and then retrieved to update the user interface. Seeing the complete flow made the overall design much easier to understand.      The solo portion of the lab was incredibly valuable because it made me have to think about how to implement the different pieces so they could communicate correctly which really reinforced how each part of the application fits together. Working through the implementation myself helped me understand the mechanics instead of just following along with examples.     ...
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cst438 - week1

     This week was a nice introduction to the course along with some of the services we'll be using, specifically spring boot. I really enjoyed the labs because they gave me a chance to become familiar with spring boot again and refresh my understanding of its components. It was a good balance of reviewing concepts I had seen before while also preparing me for the rest of the course.      Before this week, I thought of software engineering primarily as the process of designing and integrating large systems. In my mind, software development was focused on writing the individual pieces of code, while software engineering was about connecting those pieces through APIs, microservices, and overall system architecture. After this week, I still think those ideas are an important part of software engineering, but I've realized that the development workflow is just as important. The processes, tools, and teams use to build software efficiently are a major part of en...
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cst383 - week 7

     This week focused on encoding categorical variables, logistic regression, and overfitting. While the lectures introduced several important machine learning concepts, I think the homework was what helped reinforce them the most. Unlike many previous assignments, this one was much more open ended and required me to make my own decisions about how to approach the problem. We were given a dataset and told to predict a target variable using machine learning practices that we've learned, so how to go about preprocessing the data and tuning the model was left to me.      Initially the open endedness of the assignment made it a bit more challenging with not having a clear step by step process to follow, but it certainly made the assignment feel much more realistic seeing as in an actual career, problems arent going to be presented with exact instructions. Being able to evaluate different approaches is an important skill to train. I felt that I had made good d...
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cst383 - week 6

     This week focused on hyperparameter tuning, KNN regression, linear regression, and evaluating regression models. There was a lot to cover in these topics but interestingly enough they gave me an appreciation for what goes into creating machine learning models. From my previous perspective I think I viewed machine learning as mostly selecting an algorithm and allowing it to produce results. But in learning about these concepts like hyperparameter tuning, it showed me that there is still a significant human element involved in the process. The performance of a model can depend heavily on the choices made by the developer, and finding the right settings requires testing and careful evaluation.      Additionally the distinction between classification and regression was interesting because while both are forms of prediction, they are designed to solve different types of problems. Regression is useful in that many real world situations involve predicting nu...
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cst383 - week 5

     This week covered machine learning topics like handling missing data, data scaling, z-score calculations, knn classification, test sets, cross validation, and evaluating models. These topics, while diverse, worked well together for preparing data and testing to make sure conclusions drawn from it are accurate.     I found  learning about missing data and how it is represented interesting. I had originally not given much thought to the distinction between values like None and NaN so it was fun learning how these values behave and why they are treated differently. Data is often filled with holes and knowing how to handle missing information is an important part of the analysis process.      Cross validation was another topic that stood out to me. The idea of testing a model against different subsets of data to verify that the results are reliable seems intuitive and clever. It made me think about the people who originally developed these ...
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