AI Tools & Frameworks Directory

Robot friends collaborate to learn to fly a drone The post Deep Reinforcement Learning: The Actor-Critic Method appeared first on Towards Data Science.

Google just dropped T5Gemma-2, and it is a game-changer for someone working with AI models on everyday hardware. Built on the Gemma 3 family, this encoder-decoder powerhouse squeezes multimodal smarts and massive context into tiny packages. Imagine running 270M parameters running smoothly on your la...

This article is divided into five parts; they are: • An Example of Tensor Parallelism • Setting Up Tensor Parallelism • Preparing Model for Tensor Parallelism • Train a Model with Tensor Parallelism • Combining Tensor Parallelism with FSDP Tensor parallelism originated from the Megatron-LM paper.

From simple chat to multi-agent reasoning and real-time REST APIs The post Production-Ready LLMs Made Simple with the NeMo Agent Toolkit appeared first on Towards Data Science.

Want to level up your data science toolkit? Here are some Python libraries that'll make your work easier.

I remember from my student days the plethora of subscriptions, fees, and payments to be made for a range of tasks. Be it learning a new skill, using the right environment for practice, or simply travelling to and from home, we had to shell money out of our pockets. But it is almost 2026 now, […] The...

This article is divided into five parts; they are: • Introduction to Fully Sharded Data Parallel • Preparing Model for FSDP Training • Training Loop with FSDP • Fine-Tuning FSDP Behavior • Checkpointing FSDP Models Sharding is a term originally used in database management systems, where it refers to...

AUC measures how well a model ranks positives above negatives, independent of any chosen threshold. The post The Machine Learning “Advent Calendar” Bonus 1: AUC in Excel appeared first on Towards Data Science.

Make extra money between classes with beginner-friendly freelance platforms that fit your lifestyle.

Towards understanding if your agentic solution is actually better The post Agents Under the Curve (AUC) appeared first on Towards Data Science.

As a developer, tell me if you relate to this – Docker commands are easy to understand but difficult to apply meaningfully. Out of the countless tutorials that I followed, most stopped at syntax, leaving me unsure about what to build next. (Here is an exception – A step-by-step Docker tutorial for c...

If you've built chatbots or worked with language models, you're already familiar with how AI systems handle memory within a single conversation.

This article is divided into six parts; they are: • Pipeline Parallelism Overview • Model Preparation for Pipeline Parallelism • Stage and Pipeline Schedule • Training Loop • Distributed Checkpointing • Limitations of Pipeline Parallelism Pipeline parallelism means creating the model as a pipeline o...

How to make LLMs reason with verifiable, step-by-step logic (Part 2) The post Implementing Vibe Proving with Reinforcement Learning appeared first on Towards Data Science.

We have entered the time of multi-agent artificial intelligence. However, there is a very important issue: in what way can remote AI agents produce rich and interactive experiences without exposing the system to security risks? Google A2UI (Agent-to-UI) protocol addresses this question in a very sma...

Understanding the architecture, training pipeline and implementing TabPFN in practice The post Exploring TabPFN: A Foundation Model Built for Tabular Data appeared first on Towards Data Science.

Many AI systems focus on isolated tasks or simple prompt engineering. This approach allowed us to build interesting applications from a single prompt, but we are starting to hit a limit. Simple prompting falls short when we tackle complex AI tasks that require multiple stages or enterprise systems t...

Agent creation has become easier than ever but have you ever thought – how can we make them more powerful than they already are? I recently thought of one possible way – what if they had realtime information about specific categories like finance and movies. That would be really cool, right? While e...

The NotebookLM is a relatively new Internet phenomenon, in which Google has distinguished itself, thanks to its Audio Overview mode – a mechanism that transforms the text in the paper into a two-person podcast. All of this, in a single click. But what should you do when you wish to build it yourself...

This article is divided into two parts; they are: • Data Parallelism • Distributed Data Parallelism If you have multiple GPUs, you can combine them to operate as a single GPU with greater memory capacity.

This article is divided into two parts; they are: • Using `torch.

An intuitive explanation of transforming random variables correctly. The post Keeping Probabilities Honest: The Jacobian Adjustment appeared first on Towards Data Science.

An intuitive, step-by-step look at how Transformers use self-attention to turn static word embeddings into contextual representations, illustrated with simple examples and an Excel-friendly walkthrough. The post The Machine Learning “Advent Calendar” Day 24: Transformers for Text in Excel appeared f...

This article is divided into three parts; they are: • Floating-point Numbers • Automatic Mixed Precision Training • Gradient Checkpointing Let's get started! The default data type in PyTorch is the IEEE 754 32-bit floating-point format, also known as single precision.