Optimizing Airport Gate Assignments Using Multi Objective Reinforcement Learning (MORL) — Part 1
Author(s): Ranjith Menon Originally published on Towards AI. RL is the Gate-way to Airport Efficiency (pun intended) Ever found yourself sprinting across an airport to board a connecting flight? Or wandering endless corridors in search of your boarding gate? Efficient gate assignments …
Optimizing Supply Chain with Time Series Forecasting: A Customer-Centric Approach
Author(s): Shenggang Li Originally published on Towards AI. Using the Repurchase Predictive Model for Product Demand Forecasting This member-only story is on us. Upgrade to access all of Medium. Photo by iStrfry , Marcus on Unsplash In this paper, I explore a …
Why OpenAI’s o1 Model Is A Scam
Author(s): Artem Shelamanov Originally published on Towards AI. As a data scientist who has worked with LLMs since they were first introduced, I thought that when I heard about o1, it was a joke. When it turned out to be an actual, …
Demystifying PDF Parsing 05: Unifying Separate Tasks into a Small Model
Author(s): Florian June Originally published on Towards AI. Mechanics, Code, Insights on GOT, DLAFormer, and UNIT This member-only story is on us. Upgrade to access all of Medium. This article is the fifth in the series. The previous articles introduced several mainstream …
Regularization in Machine Learning: Mastering Ridge, Lasso, and Elastic Net
Author(s): Souradip Pal Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. The story of regularization starts with a simple yet crucial problem that haunts many machine learning models: overfitting. Picture this — you’ve …
Are Diffusion Models Really Superior to GANs on Image Super Resolution?
Author(s): Valerii Startsev Originally published on Towards AI. Photo by Kasia Derenda on Unsplash Introduction For over half a decade (2014–2020), generative adversarial networks (GANs) dominated generative modeling, including image super-resolution (ISR). The introduced adversarial training framework (involving a competing generator and …
Meta Learners: Measuring Treatment Effects with Causal Machine Learning
Author(s): Hajime Takeda Originally published on Towards AI. TL;DR: In recent years, algorithms combining causal inference and machine learning have been a hot topic. In my previous article, I discussed the basics of Causal Machine Learning. This article aims to explain Meta …
Customer Segmentation and Time Series Forecasting Based on Sales Data #1/3
Author(s): Naveen Malla Originally published on Towards AI. Customer Segmentation and Time Series Forecasting Based on Sales Data #1/3 Hey, first things first. This blog is divided into a 3-part series where I am going to focus on three different aspects: Exploratory …
Advance Slicing And Indexing + Numpy Array Walkthrough
Author(s): Adam Ross Nelson Originally published on Towards AI. Exploring advanced slicing techniques with Numpy, skimage, + Python This member-only story is on us. Upgrade to access all of Medium. When working with NumPy arrays, mastering advanced slicing techniques can greatly enhance …
#41 OpenAI’s “innovation,” LLM Quantization, Feature Selection, and more!
Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, we are sharing lots of resources covering some developments in the AI landscape. Today’s articles cover everything from the speed issues with Open AI’s new model …
Top 10 AI and LLM Trends Transforming Marketing in 2024
Author(s): Mukundan Sankar Originally published on Towards AI. Discover the top 10 AI and LLM trends transforming marketing in 2024. Learn how AI-driven strategies like generative content, hyper-personalization, and predictive analytics are revolutionizing customer engagement and marketing effectiveness. This member-only story is …
AI That Thinks Before It Speaks — OpenAI “o1” Models
Author(s): Richard Warepam Originally published on Towards AI. What is OpenAI ‘o1’? How Does It Work? When To Use o1-preview & o1-mini? This member-only story is on us. Upgrade to access all of Medium. If you are not a member, click here …
Solving Complex Business Problems with Mixed-Integer Linear Programming
Author(s): Shenggang Li Originally published on Towards AI. A Practical Exploration of MILP Applications: From Workforce Optimization to Financial Planning and Beyond This member-only story is on us. Upgrade to access all of Medium. Photo by Ruth H Curtis on Unsplash If …
TAI #117:Do OpenAI’s o1 Models Unlock a Full “Moore’s Law” Feedback Loop for LLM Inference Tokens?
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie OpenAI’s new o1 series of “reasoning” models took clear center stage this week. These models use an advanced form of search and reasoning during …
Gradient-Based Learning In Numpy
Author(s): Shashank Bhushan Originally published on Towards AI. Photo by Erol Ahmed on Unsplash What is Gradient-Based Learning? Mathematically training a neural network can be framed as an optimization problem in which we either try to maximize or minimize some function f(x). …
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