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#General #Development #Mobile Development #Cloud & DevOps #Cybersecurity & Privacy #AI & Data Science #Hardware & Gadgets #Design & UXUsing NotebookLM as Your Machine Learning Study Guide
Learning machine learning can be challenging.
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10 YouTube Channels Every Aspiring Data Scientist Should Follow in 2025
Want to be a data scientist in 2025? These 10 YouTube channels teach important skills, from Python basics to advanced machine learning.
Encoders and Decoders in Transformer Models
This article is divided into three parts; they are: β’ Full Transformer Models: Encoder-Decoder Architecture β’ Encoder-Only Models β’ Decoder-Only Models The original transformer architecture, introduced in "Attention is All You Need," combines an encoder and decoder specifically designed for sequence-to-sequence (seq2seq) tasks like machine translation.
Prototyping Gradient Descent in Machine Learning
Mathematical theorem and credit transaction prediction using Stochastic / Batch GD The post Prototyping Gradient Descent in Machine Learning appeared first on Towards Data Science.
Estimating Product-Level Price Elasticities Using Hierarchical Bayesian
Using one model to personalize ML results The post Estimating Product-Level Price Elasticities Using Hierarchical Bayesian appeared first on Towards Data Science.
New to LLMs? StartΒ HereΒ
A guide to Agents, LLMs, RAG, Fine-tuning, LangChain with practical examples to start building The post New to LLMs? StartHere appeared first on Towards Data Science.
Do More with NumPy Array Type Hints: Annotate & Validate Shape & Dtype
Improve static analysis and run-time validation with full generic specification The post Do More with NumPy Array Type Hints: Annotate & Validate Shape & Dtype appeared first on Towards Data Science.
How to Evaluate LLMs and Algorithms β The Right Way
Never miss a new edition of The Variable, our weekly newsletter featuring a top-notch selection of editorsβ picks, deep dives, community news, and more. Subscribe today! All the hard work it takes to integratelarge language modelsand powerful algorithms into your workflows can go to waste if the outputs you see donβt live up to expectations. [β¦] The post How to Evaluate LLMs and Algorithms β The Right Way appeared...
Top 7 Python Frameworks for AI Agents
Design, test, and deploy multi-agent systems in hours using the powerful agentic frameworks.
A Gentle Introduction to Word Embedding and Text Vectorization
"I'm feeling blue today" versus "I painted the fence blue.
Understanding OpenAI Codex CLI Commands
We have seen a new era of agentic IDEs like Windsurf and Cursor AI.
The 3 Horizons of LLM Evolution
The shift from native LLMs (2018) to LLM agents (2025) has enabled AI to move beyond static knowledge, integrating retrieval, reasoning, and real-world interaction for autonomous problem-solving.
Multiple Linear Regression Analysis
Implementation of multiple linear regression on real data: Assumption checks, model evaluation, and interpretation of results usingPython. The post Multiple Linear Regression Analysis appeared first on Towards Data Science.
Googleβs AlphaEvolve: Getting Started with Evolutionary CodingΒ Agents
Introduction AlphaEvolve [1] is a promising new coding agent by Googleβs DeepMind. Letβs look at what it is and why it is generating hype. Much of the Google paper is on the claim that AlphaEvolve is facilitating novel research through its ability to improve code until it solves a problem in a really good way. [β¦] The post Googleβs AlphaEvolve: Getting Started with Evolutionary CodingAgents appeared first on Towards...
Inheritance: A Software Engineering Concept Data Scientists Must Know To Succeed
Coding concepts that distinguish an amateur from a professional data scientist The post Inheritance: A Software Engineering Concept Data Scientists Must Know To Succeed appeared first on Towards Data Science.
The Sun is Setting on PowerCenter Support: Whatβs Next?
As standard PowerCenter support winds down, the path forward requires careful consideration of your organization's specific needs and constraints.
What Statistics Can Tell Us About NBA Coaches
Using Python to determine where NBA coaches come from and what makes them successful The post What Statistics Can Tell Us About NBA Coaches appeared first on Towards Data Science.
About Calculating Date Ranges in DAX
When performing date calculations, creating date ranges can be helpful. But how can we do this, and which DAX function can help us in which case? Now you can learn more about this topic. The post About Calculating Date Ranges in DAX appeared first on Towards Data Science.
From Python to AI Engineer: A Self-Study Roadmap
A practical roadmap for Python programmers to develop the advanced skills, specialized knowledge, and engineering mindset needed to become successful AI engineers in 2025.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
5 Breakthrough Machine Learning Research Papers Already in 2025
Machine learning research continues to advance rapidly.
Run Python in Your Browser with PyScript: A Beginnerβs Guide
You donβt need an additional setup to run the Python web application.
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.
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.
Advancing Gemini's security safeguards
Weβve made Gemini 2.5 our most secure model family to date.
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.