You’re Just One Article Away from Building Your First ML Model (No Coding Required)
Author(s): Alex Vysotskiy Originally published on Towards AI. Zero to ML Hero: A Beginner’s Guide to Vertex AI for Non-Coders When you hear “Machine Learning,” do you immediately think of complicated algorithms, endless coding, and intimidating data science jargon? Me too — …
What Is Overfitting in Machine Learning?Overfitting in ML Explained Simply with Real Examples | M005
Author(s): Mehul Ligade Originally published on Towards AI. What Is Overfitting in Machine Learning?Overfitting in ML Explained Simply with Real Examples | M005 📍 Abstract If you have ever trained a machine learning model that gave you a perfect-looking score — and …
The Essential Guide to Model Evaluation Metrics for Classification
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by Europeana on Unsplash Introduction Classification is one of the most common machine learning tasks, where models predict discrete categories or classes. Examples include detecting fraud, diagnosing diseases, or filtering spam emails. To …
Introduction to RAG: Basics to Mastery. 3-Agentic RAG-Giving Your Retrieval Pipeline a Brain
Author(s): Taha Azizi Originally published on Towards AI. Part 3 of the mini-series introduction to RAG Introduction In the last two articles, we built: A basic RAG Pipeline with semantic search. A Hybrid RAG that combined keyword + semantic search. Now we’re …
Why Ethics in AI Matters: Tackling Bias and Building Fair Machine Learning Systems
Author(s): Yuval Mehta Originally published on Towards AI. Photo by Christian Lue on Unsplash After learning that a test AI hiring tool discriminated against resumes that contained the word “women’s,” Amazon quietly discontinued it in 2018. The model had successfully taught itself …
What is Reinforcement Learning? A Deep and Practical Guide to the Most Powerful Idea in AI | M006
Author(s): Mehul Ligade Originally published on Towards AI. What is Reinforcement Learning? A Deep and Practical Guide to the Most Powerful Idea in AI | M006 📍 Abstract Reinforcement Learning is one of those terms that gets thrown around in the world …
From Pandas to PySpark: My Journey into Big Data Processing
Author(s): Yuval Mehta Originally published on Towards AI. Photo by Joshua Sortino on Unsplash Working with gigabytes or even terabytes of data is no longer a challenge exclusive to computer giants or scientific labs in the era of big data. These days, …
Task Arithmetic for Model Editing
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by charlesdeluvio on Unsplash Introduction In the 2004 film “Eternal Sunshine of the Spotless Mind,” Clementine (played by Kate Winslet) and Joel (played by Jim Carey) visit Lacuna Inc. to undergo a revolutionary …
An Essential Guide for Generative Models Evaluation Metrics
Author(s): Ayo Akinkugbe Originally published on Towards AI. Photo by Europeana on Unsplash Introduction Generative models are everywhere – The most popular being LLMs. However generative tasks span generating realistic photos (eg. GANs, Diffusion models), to creating text (eg. large language models), …
Why You May Not Need Fine-Tuning for Your Use Case!
Author(s): Vaishnavi Seetharama Originally published on Towards AI. In recent years, fine-tuning large language models (LLMs) like GPT-4 or later has become a popular trend among developers, data scientists, and enterprises. The idea of molding a powerful general‑purpose model to your exact …
How to Build Bulletproof Data Pipelines with PySpark That Actually Scale
Author(s): Yuval Mehta Originally published on Towards AI. Photo by Claudio Schwarz on Unsplash We’re past the era when a CSV, a Pandas DataFrame, and a single machine could handle everything you threw at them. Data is heavier now. It arrives fast, …
Bank Wealth Planning — Dynamic AI “Broker Guider” Platform
Author(s): Shenggang Li Originally published on Towards AI. Real-time, constraint-aware portfolio rebalancing for advisors and clients This platform adjusts portfolio weights to each investor’s goals while honoring risk, liquidity, turnover, and tax rules. It ingests client profiles and live market data, then …
I Ran OpenAI’s New Open Model on My Laptop to Extract Medical Data — Here’s What Happened
Author(s): Marie Humbert-Droz, PhD Originally published on Towards AI. Testing privacy-first healthcare AI with OpenAI’s first open-weight models OpenAI just released its first family of open-weight models, and I couldn’t resist testing them on one of healthcare’s trickiest problems: extracting structured data …
Beyond Associations: Reinforcement Learning for Sequential Market Basket Decisions
Author(s): Shenggang Li Originally published on Towards AI. Clustered contextual bandits and tabular Q-learning with off-policy evaluation on real-world retail logs Traditional market basket analysis (MBA) explains what tends to co-occur, but it does not decide what to do next. This paper …
“Unlock the power of Principal Component Analysis (PCA) with this step-by-step guide. Explore dimensionality reduction and data insights with clarity and ease.”
Author(s): Ajay Kumar mahto Originally published on Towards AI. A Step-by-Step Journey Through Dimensionality Reduction and Data Exploration In simple terms, PCA (Principal Component Analysis) is a technique used to simplify and understand complex data. It takes a dataset with many variables …
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