Baines Blogging

  Let’s be honest — when people hear “data analysis” , they often picture spreadsheets, endless rows of numbers, and someone yawning behind a laptop at 2 a.m. But that’s a myth. Data analysis isn’t dull — it’s detective work, creativity, and storytelling rolled into one. If you’ve ever dismissed it as boring, it’s time to think again. Here are 7 reasons why data analysis is anything but boring: 1. You Get to Solve Real-World Mysteries Data analysts are like modern-day detectives. Every dataset hides clues that reveal why something happened or how it could change. Whether it’s uncovering why sales dipped last quarter or predicting the next big trend, you’re constantly piecing together a puzzle — and few things are more satisfying than cracking the case. 2. It’s a Gateway to Understanding Human Behavior Data tells stories about people — what they buy, how they think, where they spend their time. Analysing data gives you a front-row seat to human patterns and decision-making...

Beginners guide for using the Machine Learning and/or AI tools on google.colab for a complete beginner:  AI and ML is all about analysing data so first you need to decide what kind of data you want to analyse. ( I refer you back to my previous blog post beginners guide to AI and ML terms. .) Basically do you want to analyse numerical data , text or images ? On this occasion I’m going to keep it simple and create some data visualisations  (graphs) You can get free open source data from this website kaggle.com I downloaded this file in .csv format: s-p-500-time-series-forecasting-with-prophet/input   Next find this website colab.research.google.com https://colab.research.google.com This is when you can go to chatgpt and ask it to write the code for google colab to analyse the data in  the way you want for example you could ask it to write the code to create a dataframe from that data:    Drag and drop the csv file into google.colab Change the labels s...

📶💻💹 Artificial Intelligence (AI) and Machine Learning (ML) are terms that are used by a lot of people but do you know about the technical nuts and bolts of how they actually work? If you don't that's OK, — I’ve broken down some of the most common terms you might hear in the world of AI/ML into simple explanations anyone can understand. Plus, if you're using Google Colab , there's a built-in AI assistant called Gemini that can help you understand and write code but you need to know the right questions to ask it first.   1. NLP (Natural Language Processing) 🎤🎧 NLP is a branch of AI that helps computers understand and work with human language. Think of it as the technology behind things like chatbots, language translators, and voice assistants like Siri or Alexa. It allows machines to “read” and make sense of text or speech, just like we do. 2. BERT (Bidirectional Encoder Representations from Transformers) BERT is a special AI model developed by Google that he...

Unlocking the Power of Data Analysis: Tools and Techniques for Understanding User Feedback Data analysis is the backbone of decision-making across countless industries, providing insights that drive business strategy, marketing decisions, and customer experience improvements. With the explosion of user-generated content on platforms like YouTube, analyzing user comments has become a powerful tool to understand public sentiment, track brand reputation, and improve user engagement. Step 1: Data Collection – Pulling User Comments from YouTube Before any analysis can happen, we first need the data. In the case of YouTube, user comments are stored publicly on each video. To collect them, we use the YouTube Data API . This API allows us to programmatically retrieve comment data, such as the text of the comments, the date posted, and user metadata (like user ID or username). Here’s how it works: Set up the API : First, you’ll need to create a project on the Google Cloud Console, enab...