Deep Dives

Beyond Model Stacking: The Architecture Principles That Make Multimodal AI Systems Work

1. It with a Vision While rewatching , I discovered myself captivated by how deeply JARVIS could understand a scene. It wasn’t just recognizing objects, it understood context and described the scene in natural...

Beyond Code Generation: Repeatedly Evolve Text with LLMs

the initial response from an LLM doesn’t suit you? You rerun it, right? Now, if you happen to were to automate that… success = false while not success: response = prompt.invoke() ...

Landing your First Machine Learning Job: Startup vs Big Tech vs Academia

This guide is for early-stage Machine Learning practitioners who've just graduated from university and at the moment are in search of full-time roles within the Machine Learning field. A lot of the experiences shared...

Prescriptive Modeling Unpacked: A Complete Guide to Intervention With Bayesian Modeling.

In this text, I'll reveal tips on how to move from simply forecasting outcomes to actively intervening in systems to steer toward desired goals. With hands-on examples in predictive maintenance, I'll show how data-driven...

Constructing a Modern Dashboard with Python and Gradio

second in a brief series on developing data dashboards using the newest Python-based GUI development tools, Streamlit, Gradio, and Taipy.  The source dataset for every dashboard will likely be the identical, but stored in...

Agentic RAG Applications: Company Knowledge Slack Agents

I that almost all corporations would have built or implemented their very own Rag agents by now. An AI knowledge agent can dig through internal documentation — web sites, PDFs, random docs — and...

Detecting Malicious URLs Using LSTM and Google’s BERT Models

The rise of cybercrime has made fraudulent webpage detection a necessary task in ensuring that the web is protected. It is clear that these risks, equivalent to the theft of personal information, malware, and...

Bayesian Optimization for Hyperparameter Tuning of Deep Learning Models

to tune hyperparamters of deep learning models (Keras Sequential model), compared with a conventional approach — Grid Search. Bayesian Optimization Bayesian Optimization is a sequential design strategy for global optimization of black-box functions. It is especially well-suited for...

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