Code Less, Ship Faster: Building APIs with FastAPI
Master path operations, Pydantic models, dependency injection, and automatic documentation.
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Do you build GenAI systems and want to deploy them, or do you just want to learn more about FastAPI? Then this is exactly what you were looking for! Just imagine you have lots of PDF reports and want to search for specific answers in them. Either you could spend hours scrolling, or you could […]
The...
Grow your LinkedIn Scarily Fast (For Data Scientists) with This AI Workflow
What if I told you, you often lose your next big role to someone much less credible than you? Unjust, yes, but certainly not untrue. Here is the reality: recruiters, founders, and collaborators don’t discover talent through Kaggle notebooks. They discover it through visibility. Visibility on the wor...
Zero-Waste Agentic RAG: Designing Caching Architectures to Minimize Latency and LLM Costs at Scale
Reducing LLM costs by 30% with validation-aware, multi-tier caching
The post Zero-Waste Agentic RAG: Designing Caching Architectures to Minimize Latency and LLM Costs at Scale appeared first on Towards Data Science.
If you have both unique domain expertise and know how to make it usable to your AI systems, you’ll be hard to beat.
The post Context Engineering as Your Competitive Edge appeared first on Towards Data Science.
Claude Skills and Subagents: Escaping the Prompt Engineering Hamster Wheel
How reusable, lazy-loaded instructions solve the context bloat problem in AI-assisted development.
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Scaling ML Inference on Databricks: Liquid or Partitioned? Salted or Not?
A case study on techniques to maximize your clusters
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You must have faced the never-ending wait of an AI model taking its time to answer your query. To put an end to this wait, the new Mercury 2 reasoning model of Inception Labs is now live. It works a bit differently from others. It employs diffusion to provide quality answers at nearly instant speed....
Can LLM Embeddings Improve Time Series Forecasting? A Practical Feature Engineering Approach
Using large language models (LLMs) — or their outputs, for that matter — for all kinds of machine learning-driven tasks, including predictive ones that were already being solved long before language models emerged, has become something of a trend.
Nano Banana 2: Google’s latest AI image generation model
Nano Banana! The image model that took the world by storm just got eclipsed by…itself. Yes! Google did it again. After establishing standards by their release of Nano banana, they are back with its high anticipated follow-up: Nano Banana 2 (officially designated as Gemini 3.1 Flash Image). This new ...
Google Launches Nano Banana 2: Learn All About It!
Nano Banana! The image model that took the world by storm just got eclipsed by…itself. Yes! Google did it again. After establishing standards by their release of Nano banana, they are back with its high anticipated follow-up: Nano Banana 2 (officially designated as Gemini 3.1 Flash Image). This new ...
Designing Data and AI Systems That Hold Up in Production
A system-level perspective on architecture, agents, and responsible scale
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A practical guide to identifying, restoring, and transforming elements within your images
The post Detecting and Editing Visual Objects with Gemini appeared first on Towards Data Science.
Scaling Feature Engineering Pipelines with Feast and Ray
Utilizing feature stores like Feast and distributed compute frameworks like Ray in production machine learning systems
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Breaking the Host Memory Bottleneck: How Peer Direct Transformed Gaudi’s Cloud Performance
Engineering RDMA-like performance over cloud host NICs using libfabric, DMA-BUF, and HCCL to restore distributed training scalability
The post Breaking the Host Memory Bottleneck: How Peer Direct Transformed Gaudi’s Cloud Performance appeared first on Towards Data Science.
Aliasing in Audio, Easily Explained: From Wagon Wheels to Waveforms
Understanding the foundational distortion of digital audio from first principles, with worked examples and visual intuition
The post Aliasing in Audio, Easily Explained: From Wagon Wheels to Waveforms appeared first on Towards Data Science.
Optimizing Token Generation in PyTorch Decoder Models
Hiding host-device synchronization via CUDA stream interleaving
The post Optimizing Token Generation in PyTorch Decoder Models appeared first on Towards Data Science.