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10 Underrated Books for Mastering Machine Learning
If you've been into machine learning for a while, youβve probably noticed that the same books get recommended over and over again.
Published on: May 22, 2025 | Source:
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Gemma 3n: Smarter, Faster, and Offline-Ready
Discover the new AI architecture that lets you run AI models directly on phones, laptops, and tablets, redefining efficiency and multimodal capabilities.
Published on: May 22, 2025 | Source:Top Machine Learning Jobs and How to Prepare ForΒ Them
Explaining the different machine learning roles The post Top Machine Learning Jobs and How to Prepare ForThem appeared first on Towards Data Science.
Published on: May 22, 2025 | Source:Use PyTorch to Easily Access Your GPU
Or⦠how an ML library can accelerate non-ML computations The post Use PyTorch to Easily Access Your GPU appeared first on Towards Data Science.
Published on: May 21, 2025 | Source:Building AI Applications in Ruby
Why Ruby may be the best language to write your next AI web application The post Building AI Applications in Ruby appeared first on Towards Data Science.
Published on: May 21, 2025 | Source:Choosing the Right Machine Learning Algorithm: A Decision Tree Approach
Amid so many different machine learning algorithms to choose from. This guide has been designed to help you navigate towards the right one for you, depending on your data and the problem to address.
Published on: May 21, 2025 | Source:Surprising Things You Can Do with Pythonβs csv Module
Think it's just for reading simple tables? See what else you can do with this Python standard library module.
Published on: May 21, 2025 | Source:10 Python One-Liners for Feature Selection Like a Pro
In many data analysis processes, including machine learning , data preprocessing is an important stage before further analysis or model training and evaluation.
Published on: May 21, 2025 | Source:What the Most Detailed Peer-Reviewed Study on AI in the Classroom Taught Us
A meta analysis that turns out positive yet identifies the need for further research The post What the Most Detailed Peer-Reviewed Study on AI in the Classroom Taught Us appeared first on Towards Data Science.
Published on: May 20, 2025 | Source:I Teach Data Viz with a Bag of Rocks
Here's Why Domain-Specific Integration Matters in Your Data Science Workflows The post I Teach Data Viz with a Bag of Rocks appeared first on Towards Data Science.
Published on: May 20, 2025 | Source:5 Breakthrough Machine Learning Research Papers Already in 2025
Machine learning research continues to advance rapidly.
Published on: May 20, 2025 | Source:Run Python in Your Browser with PyScript: A Beginnerβs Guide
You donβt need an additional setup to run the Python web application.
Published on: May 20, 2025 | Source:7 Python Functions Youβre Probably Misusing (And Donβt Realize It)
These common Python functions seem simpleβ¦ until they arenβt. Avoid subtle bugs by learning how to use them the right way.
Published on: May 20, 2025 | Source:Gemini 2.5: Our most intelligent models are getting even better
Gemini 2.5 Pro continues to be loved by developers as the best model for coding, and 2.5 Flash is getting even better with a new update. Weβre bringing new capabilities to our models, including Deep Think, an experimental enhanced reasoning mode for 2.5 Pro.
Published on: May 20, 2025 | Source:Advancing Gemini's security safeguards
Weβve made Gemini 2.5 our most secure model family to date.
Published on: May 20, 2025 | Source:Our vision for building a universal AI assistant
Weβre extending Gemini to become a world model that can make plans and imagine new experiences by simulating aspects of the world.
Published on: May 20, 2025 | Source:Announcing Gemma 3n preview: Powerful, efficient, mobile-first AI
Gemma 3n is a cutting-edge open model designed for fast, multimodal AI on devices, featuring optimized performance, unique flexibility with a 2-in-1 model, and expanded multimodal understanding with audio, empowering developers to build live, interactive applications and sophisticated audio-centric experiences.
Published on: May 20, 2025 | Source:Fuel your creativity with new generative media models and tools
Introducing Veo 3 and Imagen 4, and a new tool for filmmaking called Flow.
Published on: May 20, 2025 | Source:SynthID Detector β a new portal to help identify AI-generated content
Learn about the new SynthID Detector portal we announced at I/O to help people understand how the content they see online was generated.
Published on: May 20, 2025 | Source:The Ultimate Guide to Learning Anything with NotebookLM
Learn about turning your notes and sources into a personalized, AI-powered tutor with NotebookLM.
Published on: May 19, 2025 | Source:WTF is Language Model Quantization?!?
Unveiling the origins, "ins and outs," and implications of quantization in language models: all in simple terms.
Published on: May 19, 2025 | Source:7 Best FREE Platforms to Host Machine Learning Models
Built an ML model? Here are 7 free platforms to share it with the world.
Published on: May 19, 2025 | Source:How to Set the Number of Trees in Random Forest
A practical introduction to the optRF package The post How to Set the Number of Trees in Random Forest appeared first on Towards Data Science.
Published on: May 16, 2025 | Source:How to Build an AI Journal with LlamaIndex
A step-by-step guide for building an AI assistant powered by LlamaIndex The post How to Build an AI Journal with LlamaIndex appeared first on Towards Data Science.
Published on: May 16, 2025 | Source:The Automation Trap: Why Low-Code AI Models Fail When You Scale
Low-code AI platforms promise speed, a model without a single line of code. But when you try to scale them, they deliver something else: silent crashes, cryptic failures, and models that choke under pressure. The post The Automation Trap: Why Low-Code AI Models Fail When You Scale appeared first on Towards Data Science.
Published on: May 16, 2025 | Source:Agentic AI 102: Guardrails and Agent Evaluation
An introduction to tools that make your model safer and more predictable and performant. The post Agentic AI 102: Guardrails and Agent Evaluation appeared first on Towards Data Science.
Published on: May 16, 2025 | Source:A Guide to Mastering Serverless Machine Learning
Discover the what, why, and how of serverless machine learning with the interactive course GitHub repository.
Published on: May 16, 2025 | Source:A Gentle Introduction to Learning Rate Schedulers
Ever wondered why your neural network seems to get stuck during training, or why it starts strong but fails to reach its full potential? The culprit might be your learning rate β arguably one of the most important hyperparameters in machine learning.
Published on: May 16, 2025 | Source:Qwen2.5-Omni is a Powerhouse: A Guide with Demo Project
This article guides you throughout a demo project to set up and run an instance of this powerful multi-modal model in a Python script or notebook.
Published on: May 16, 2025 | Source:Googleβs AlphaEvolve IsΒ EvolvingΒ New Algorithms β And It Could Be a Game Changer
A blend of LLMs' creative generation capabilities with genetic algorithms The post Googleβs AlphaEvolve IsEvolvingNew Algorithms β And It Could Be a Game Changer appeared first on Towards Data Science.
Published on: May 16, 2025 | Source:Understanding Random Forest using Python (scikit-learn)
A Random Forest is a powerful machine learning algorithm that can be used for classification and regression, is interpretable, and doesnβt require feature scaling. Hereβs how to apply it. The post Understanding Random Forest using Python (scikit-learn) appeared first on Towards Data Science.
Published on: May 16, 2025 | Source:How to Learn the Math Needed for MachineΒ Learning
A breakdown of the three fundamental math fields required for machine learning: statistics, linear algebra, and calculus. The post How to Learn the Math Needed for MachineLearning appeared first on Towards Data Science.
Published on: May 16, 2025 | Source:How To Build a Benchmark for Your Models
The Importance of Building a Benchmark and How To Do It The post How To Build a Benchmark for Your Models appeared first on Towards Data Science.
Published on: May 15, 2025 | Source:πͺπͺπ Lessons in Decision Making from the Monty Hall Problem
A journey into three intuitions: Common, Bayesian and Causal The post Lessons in Decision Making from the Monty Hall Problem appeared first on Towards Data Science.
Published on: May 15, 2025 | Source:Building AI Agents? A2A vs. MCP Explained Simply
Confused by AI agent frameworks? This article makes sense of A2A and MCP.
Published on: May 15, 2025 | Source: