Using GPT Vision to interpret and aggregate image data. Photo by David Travis on Unsplash.Integrating visual inputs like images alongside text and speech into large language models (LLMs) is considered an important new direction in AI research by many experts in the field. By augmenting these models to handle multiple modes of data beyond just…
Photo by Jason Goodman on UnsplashHow to up-level your structured problem solving skills and communication skills So you have brushed up on ML concepts, practiced Python and SQL for months, you think you are done with interview prep. But you might be missing the most important and hardest-to-prepare-for part of the interview — problem-solving skills.…
My learnings from Databricks customer engagements Figure 1: a technical diagram of how to write apache spark. Image by author.At Databricks, I help large retail organizations deploy and scale data and machine learning pipelines. Here are the 8 most important spark tips/tricks I’ve learned in the field. Throughout this post, we assume a general working…
A comprehensive guide to the best open-source GIS software 11 min read · 14 hours ago Photo by Louis Hansel on UnsplashMore than 10 years when I started my data career as a GIS (Geographic Information System) analyst, two pieces of do-it-all GIS software were prominent. 10 years later, it is still…
Here we won’t start from scratch. As stated earlier, we already developed the code that builds a Pyomo model of the TSP and solves it in sprint 3. And trust me, that was the hardest part. Now, we have the easier task of organizing what we did in a way that makes it general, hiding…
Additionally, Gaussian splatting doesn’t involve any neutral network at all. There isn’t even a small MLP, nothing “neural”, a scene is essentially just a set of points in space. This in itself is already an attention grabber. It is quite refreshing to see such a method gaining popularity in our AI-obsessed world with research companies…
The recent exponential advances in natural language processing capabilities from large language models (LLMs) have stirred tremendous excitement about their potential to achieve human-level intelligence. Their ability to produce remarkably coherent text and engage in dialogue after exposure to vast datasets seems to point towards flexible, general purpose reasoning skills. However, a growing chorus of…
When I began my data science journey in grad school, I had a naive view of the discipline. Namely, I was hyper-focused on learning tools and technologies (e.g. LSTM, SHAP, VAE, SOM, SQL, etc.) While a technical foundation is necessary to be a successful data scientist, focusing too much on tools creates the “Hammer Problem”…
Math behind this parameter efficient finetuning method Fine-tuning large pre-trained models is computationally challenging, often involving adjustment of millions of parameters. This traditional fine-tuning approach, while effective, demands substantial computational resources and time, posing a bottleneck for adapting these models to specific tasks. LoRA presented an effective solution to this problem by decomposing the update…
1. Choosing a Chatbot As simple as this one may sound, it is far from a trivial question. The options are manifold and include choosing to build your own chatbot using open-sourced code.[1] Using one of the gazillion chatbot APIs offered on the market, that allow you the simplest and quickest ready-set-go set-up.[2] Finetuning your…