Week Boston Housing DataSet 4364

I recently worked on the Boston Housing dataset using Google Colab, and it was a good hands-on way to learn machine learning. I used PyTorch to build a simple model that predicts house prices based on different features like number of rooms and location data. I started by loading the dataset, splitting it into training and testing data, and scaling it so the model could learn better. Then I turned the data into tensors, which PyTorch uses to run calculations .

After that, I built a basic neural network with one hidden layer and trained it using a loss function and an optimizer. Over time, the model improved its predictions by lowering the error. At the end, I tested the model to see how well it worked on new data.

I also used Google Gemini to help me understand parts of the code and fix mistakes. It made things easier when I got stuck, but I still had to understand what was going on. Overall, this project helped me better understand how machine learning models are built and trained in a simple way

 

Week 5 Language Modeling 4364

For this exercise, I used Google Colab and uploaded the code to run the language modeling section from Chapter 5. The goal was to help the computer learn patterns in text and understand how language works. When I ran the code, I was able to load the dataset and see rows of data like names, age, gender, and other information. This showed me that my code was working and that the data loaded correctly.

After that, I went through the steps to clean and prepare the data so the model could actually use it. This included organizing the data and making it easier for the computer to understand. Seeing the dataset clearly in Colab helped me understand what the model is working with before it even starts learning.

Overall, this exercise helped me better understand how data is loaded, cleaned, and prepared for AI models. It also gave me a better idea of how language modeling works behind the scenes and how computers can learn patterns in text to do things like predict words or generate sentences.

Week 4 4364 Python Code

 When I used Google Colab, I worked through a simple machine learning example where I built a linear regression model using Python. At first the code looked like a lot, but once I actually ran it step by step, it became way easier to understand.

The code started by importing a few libraries that help with different things. NumPy helps create and handle data, Matplotlib is used for making graphs, and Scikit-learn is what helps build the actual model. Then the code created some fake data to practice with, which made it easier to see how everything works without needing a real dataset.

Next, the data was split into two parts: training and testing. The training data is what the model learns from, and the testing data is used to check how well it actually works. This helped me understand that the model isn’t just memorizing numbers, it’s trying to learn a pattern.

After that, the model was created using linear regression. Basically, it tries to draw the best line through the data points. Once it was trained, it made predictions using the test data, which was cool to see because the model was actually “guessing” values.

At the end, everything was graphed. You could see the real data points and the predicted ones, along with the line the model created. This made it really easy to understand how close the model was to being correct.

Overall, this example helped me get a better understanding of how machine learning works in a simple way. Instead of just reading about it, I actually got to see how a model is built, trained, and tested in real time.

Week 3 4364 Python and Gemini

 In my predictive analytics class, Python has been really helpful for making Excel data easier to understand. Instead of just looking at a spreadsheet, I upload my files into Google Colab and use Python to work with the data. I use tools like pandas to organize everything, and then I make graphs using matplotlib so I can actually see trends. It’s way easier to understand what’s going on when you can see it instead of just reading numbers.

I’ve used this a lot when I need to compare things or look at changes over time. Instead of building charts in Excel, I can write a little bit of code and make cleaner graphs faster. Once you get used to it, it saves time because you can reuse the same code for different assignments.

I also use Google Gemini to help me when I get stuck. If I don’t know how to write something or I get an error, I’ll use it to help fix my code or show me what to do. It’s kind of like having someone help you through it. I still make sure I understand what’s going on, but it definitely makes things quicker and less confusing.

Overall, using Python has made my class a lot easier and more interesting. Turning Excel data into graphs and having help from Gemini makes everything way more manageable.

Week 2 4364

 ChatGPT is a really helpful tool that I use a lot, especially for school, but other tasks as well. It’s kind of like having someone there to help whenever I need it. The chapter talks about how it can answer questions and help with writing, but I mostly use it to understand things better and make my work easier to complete.

I use ChatGPT a lot in my business classes like predictive analytics and strategic management. In analytics, it helps me break down problems and understand what the numbers actually mean in simple terms. Instead of just doing the math, it helps me see what the results are saying. In strategic management, I use it more to help with ideas, like understanding business strategies, analyzing companies, and adding more detail to my answers.

I also use ChatGPT when I get stuck. Instead of just sitting there confused, I ask it to explain things in an easier way or give me real-life examples. I use it for writing too, like turning my ideas into better paragraphs, adding more detail, or making my wording sound smoother.

Another way I use it is to get started on assignments. Sometimes I don’t know how to begin, so I use it to help organize my thoughts or give me a starting point. It makes everything faster and less stressful. Overall, I don’t use ChatGPT to do my work for me, but to help me understand things better and do a better job on my assignments.

Week 1 4364

 Hi, my name is Aidan Werth. I am a business analytics major at the Lisle campus. I am a senior and have concluded my basketball career here about a month ago. This is my 3rd BALT class taken relating to AI, ChatGPT, and dealing with some Python as well. I have taken away many great lessons, but the biggest thing I have learned is how important it is to use AI to your advantage. Companies are implementing AI in many different aspects of how they complete work. The biggest worry is that AI is going to replace many jobs. While this is somewhat true, there is also some falsity to it. AI is replacing some jobs, and it is beneficial to companies because of how efficient and accurate it is. The falsity to it is though that while it is replacing jobs, it is also creating many jobs too. This is why it is so important to have knowledge about AI and learning how to manipulate it and use it your advantage. Overall, I am excited to learn more about AI and tools on how to use it to my advantage.