Hi, If you were expecting it to be an intuitive UI, then you probably want one of the App Store apps; a decent one is called ‘Draw Things’ and it’s free. We will use ComfyUI, an advanced AI image generator. It’s easy to install for Windows and comes with a direct download. For Mac, however,… Continue reading A decent UI for diffusion models on Apple silicon
Tag: Machine Learning
Using LLMs Locally with LM Studio.
Yew, LM Studio provides an easy to use GUI to try and test several models because it has a search to discover new models within the tool. It allows people to locally run and download GGUF models. These models are usually available quantized which requires a lot less memory. Quantized models just mean they represent… Continue reading Using LLMs Locally with LM Studio.
Setting Up Your Data Science Environment on Apple Mac Silicon: A Step-by-Step Guide with MLX Installation.
Namast, Will keep this one short and sweet. Boot up your Mac (book, mini, studio, etc.) Go here: https://brew.sh/ What is it? It’s a package manager that lets you install things via terminal easily. Install via terminal by copy pasting their install Homebrew command. We’ll use it to install our Python environment. You can use… Continue reading Setting Up Your Data Science Environment on Apple Mac Silicon: A Step-by-Step Guide with MLX Installation.
Playing Games with Reinforcement Learning
Bonjours! Who wants to land on the moon? Perhaps guided by an artificial intelligent agent? I’ll quickly go over using one of the easiest reinforcement learning libraries so you can train a Rocketship to land on the moon (or a moon). We’ll be training a deep learning model to play a game called lunar lander.… Continue reading Playing Games with Reinforcement Learning
Fashion MNIST and why it’s better than MNIST for modern Computer Vision
Hey. Many people are familiar with MNIST, if you aren’t then it is a dataset consisting of handwritten digits from 0 to 9. It stands for Modified National Institute of Standards and Technology. It’s frequently used in training computer vision models to benchmark various classification algorithms. Grad projects and research papers alike use it to… Continue reading Fashion MNIST and why it’s better than MNIST for modern Computer Vision
Unsupervised machine learning to cluster user data
Ohaio, It is interesting to analyse segments created by algorithms. Product managers and marketers will find it a somewhat unbiased way to make sense of customer data. The algorithms can work well but it helps to have a sufficient grasp of statistics and understand the limitations of each model. I thought it would be useful… Continue reading Unsupervised machine learning to cluster user data
Robust Principal Component Analysis for everyone
Bonjour Most people have heard of Principal Component Analysis. It was the last thing I learned and perhaps many people learn in their introductory linear algebra course at university. I’ve had to use it plenty of times to reduce dimensions when staring at a dataset with too many columns. Many people are satisfied with vanilla… Continue reading Robust Principal Component Analysis for everyone
Decomposing ARKK portfolio returns into factors
Hi, Some people like to watch the world burn. I’m not one of those people. I like to watch it dismantle. That is why we’ll be linear dismantling returns from an expensive ETF or maybe a mutual fund. If a person invests in mutual funds or pays a fund manager a fee, it is the… Continue reading Decomposing ARKK portfolio returns into factors
NLP for analysts, marketers and product managers
Hai I use NLP a lot, whether it has been to analyse customer survey data or to get insights from news articles and social media posts to find stock picks or create financial models. Using NLP for work can be as hard or as easy as you’d like it to be. To follow along you’d… Continue reading NLP for analysts, marketers and product managers
Creating your data science environment
Do you have a Python environment? Hai I notice a lot of people start with installing anaconda and never go past using the base data science environment. Even if you manage to create an environment it might not show up in Jupyter Labs or VSC (what I use). This should get you started pretty quickly… Continue reading Creating your data science environment