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Getting Started with NumPy: A Powerful Tool for Data Science and Math

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In Chapter 9, I learned about NumPy , a powerful Python library used for numerical computing, data science, and machine learning. NumPy makes it easy to work with large sets of numbers by using multi-dimensional arrays called ndarrays . It also comes with a huge set of mathematical functions, so you can do things like trigonometry, logarithms, and linear algebra without needing to learn all the complicated math behind it. Some other cool features include broadcasting , which lets you perform operations on arrays of different sizes, and tools for Fourier analysis . Overall, NumPy is an essential tool if you want to work with data or do scientific computi ng in Python. We also got to see a basic example of NumPy in action by generating 1,000 random numbers and then calculating the mean and standard deviation using NumPy functions. It showed how easy it is to load data into an array and quickly perform calculations without a lot of extra coding. The example was simple, but it made it c...
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Exploring the Research and Recommendation Powers of ChatGPT

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ChatGPT is a versatile tool that supports research by offering users a wide range of helpful functions. It can summarize long articles or papers, fact-check data, extract relevant keywords, and suggest reliable sources. For deeper understanding, it also helps answer detailed questions, generate citations, and organize content into easy-to-read formats. Though it doesn’t access real-time data, it uses a massive base of pre-trained knowledge to help users explore topics like electric vehicles, offering both advantages (e.g., zero emissions, lower costs) and disadvantages (e.g., limited range, charging infrastructure). While powerful, users should always cross-check ChatGPT’s outputs and think critically about the information. Beyond research, ChatGPT also excels at generating personalized recommendations in many areas. Whether you're looking for a good book, planning a trip, trying to pick software, or working on self-improvement, it can suggest tailored ideas based on your preferen...
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The Growing Importance of Automation in the Workplace

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In today's workplace, automation has emerged as a key factor in fostering creativity, efficiency, and productivity. Automation technologies offer a response to the growing strain on businesses to maintain their competitiveness by decreasing human error and optimizing processes. This makes it possible for businesses to concentrate resources on more worthwhile projects, which eventually spurs growth. Automation has become essential due to factors including increased labor costs, worldwide rivalry, and developments in artificial intelligence. Businesses who use automation technology will have a major advantage in terms of speed and accuracy as sectors continue to change. Automation includes technologies like industrial automation, robotic process automation (RPA), and artificial intelligence (AI), each offering unique applications to improve business processes. RPA, for example, allows businesses to automate repetitive tasks like data entry and customer service inquiries, freeing up e...
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Week 3 - The Importance of Features and Normalization in Data Science

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Features are the quantifiable characteristics of an object or phenomenon in data science and machine learning. They make up a dataset's columns, with each row denoting an observation. They are also referred to as variables or attributes. For example, elements in a housing dataset can include the age of the property, the number of bedrooms, and the square footage. These qualities are essential for developing predictive models because they enable algorithms to spot trends and generate precise forecasts. However, for the best model performance, characteristics must be standardized because they frequently have disparate scales and units. A method for scaling features to a common range, usually between 0 and 1, is called normalization. By ensuring that each feature makes an equal contribution to the learning process, this transformation keeps one feature from taking over the model because of its size. Additionally, it decreases numerical instability, increases interpretability, and impr...
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Week 2 - Python Control Structures and Data Manipulation Summary

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Key Python programming ideas centered on data manipulation with control structures like loops and conditional statements were introduced in this reading. I discovered that while while loops keep running as long as a condition is true, for loops are helpful for repeating a block of code a predetermined number of times. Writing flexible and interactive code requires the use of conditional expressions, such as if and if-else, which enable the program to make decisions based on conditions. The significance of indentation in Python was also underlined in the reading, since it guarantees error-free code execution.  Through practical activities, I also learnt how to apply these concepts. For instance, I designed a program to distinguish between even and odd numbers, practiced writing loops to print numbers from 1 to 10, and constructed a guessing game that incorporates conditionals, loops, and user input. The usefulness of Python's adaptability in managing data and user interactions was f...
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Week 1 - Intro

My name is Tanner Tucker, and I am a senior majoring in social media marketing. Before focusing on my studies, I played football here at Benedictine University, which was a good experience that taught me the value of hard work, discipline, and teamwork. I'm excited to apply those same skills in the marketing field and learn more throughout this class. I'm looking forward to connecting with all of you and working together this semester!
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NIL in College Sports

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  NIL in College Sports With the advent of Name, Image, and Likeness (NIL) deals, college athletics in the United States have seen a substantial change. These revolutionary modifications enable collegiate athletes to profit from their own brands, whether through social media marketing, endorsements, or sponsorships. For these student-athletes, NIL has opened up a world of options, allowing them to profit monetarily from their talent and hard work. The advantages of NIL agreements are extensive. Now that college athletes may make money while still in school, it not only helps them monetarily but also teaches them important lessons about responsibility and financial literacy. These agreements may encourage outstanding players to stay in school rather than leave early for the professional ranks in order to assure financial stability, which could increase competition in college sports. Additionally, NIL agreements give non-revenue sports participants the chance to acquire visibility an...
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