Courage to Learn ML: Decoding Likelihood, MLE, and MAP

Welcome to the ‘Courage to learn ML’. This series aims to simplify complex machine learning concepts, presenting them as a relaxed and informative dialogue, much like the engaging style of “The…

towardsdatascience.com 12 hours ago

LLM and GNN: How to Improve Reasoning of Both AI Systems on Graph Data

Graph neural networks (GNNs) and large language models (LLMs) have emerged as two major branches of artificial intelligence, achieving immense success in learning from graph-structured and natural…

towardsdatascience.com 13 hours ago

Data Modelling For Data Engineers

Data modelling is an essential part of data engineering. In this story, I would like to talk about different data models, the role of SQL in data transformation and the data enrichment process. SQL…

towardsdatascience.com 13 hours ago

GenAI’s products: Move fast and fail

In Autumn 2022, I was working on a cool project. Yes, you guessed it — finetuning LLMs on company-specific data. However, soon enough, ChatGPT was released and has taken the world by storm. And what…

medium.com_towards-ai 17 hours ago

6 Free Practical LLMs Notebooks to Get Your Hands Started with LLM Applications

Embark on an exhilarating journey into the limitless possibilities of Large Language Models (LLMs) with this article, offering an exclusive lineup of six free and hands-on notebooks. Dive into the…

medium.com_towards-ai 18 hours ago

Run Local LLM Inference10x Faster (244 TOK/s): PyTorch II

Using LLaMA-7B, Pytorch analyzed the performance issues that are CPU-bound. That means the overhead is the first target to make it more efficient.. In comes the compiler. By compiling larger regions…

medium.com_towards-ai 18 hours ago

in Less than 100 Lines of Python Code

Inventory optimization is a broad problem that arises across many domains. The central question is all about figuring out: I think you are a bike shop manager. Every day, you need to contact your…

medium.com_towards-ai 18 hours ago

Introduction to Mathematical Optimisation in Python

Data Scientists tackle a wide range of real-life problems using data and various techniques. Mathematical optimisation, a powerful technique that can be applied to a wide range of problems in many…

3 Powerful Python Libraries to (Partially) Automate EDA And Get You Started With Your Data Project

To avoid the old adage of “garbage in, garbage out,” it makes sense that you should spend considerable time understanding and cleaning your data. I recently read “The Kaggle Book” by Konrad…

Version Controlling in Practice: Data, ML Model, and Code

Version control is a crucial practice! Without it, your project may become disorganized, making it challenging to roll back to any desired point. You risk losing critical model configurations…