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Cinematic, rigorous explainers. New essay every week — no listicles, no fluff.
Beyond the textbook diagrams — what a single attention head is really computing, how multi-head splits the world, and why scaling laws keep rewarding bigger context.
104 hours · 28 deep dives · diagrams, exercises, LeetCode and the calendar template that ships it.
Retrieval vs ranking, candidate generation, freshness vs relevance — the tradeoffs every real recommender lives by.
Topics, partitions, consumer groups — the parts of Kafka that actually matter when you put ML features behind it.
A long-form, primary study companion. Internals, flows, decision trees, code, and Q&A with reasoning across Spark, lakehouse, graphs, search, LLMs, RAG/agents, distributed HLD, governance, modeling, SQL, JVM, Python, K8s and CI/CD.
A comprehensive deep-dive into the data backbone powering ML, personalization, experimentation, and GenAI on modern streaming platforms
From text , generate audio files and publishing them to webapp
Deploying local python scripts and converting them as an API.
From a few initial adopters of a product, how we can target new set of users who are more likely can use the product
Exploring the fundamentals of building an .exe file from scratch, including C++ compilation, object files, linking, DLLs, and more.
CS229 provides a broad introduction to statistical machine learning (at an intermediate / advanced level) and covers supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs, practical ); and reinforcement learning among other topics
Use this prompt for gathering information all at one place
Diving deep into a Google Skill boost
Going deeper into the video rec repo Monolith and paper produced by Bytedance
A self-sufficient guide to Azure AI Foundry — what it is, how the hub/project/deployment model works, how to ship a grounded agent end-to-end with SDK + Bicep, and the security/eval/cost levers you cannot skip.
This blog explores a paper on detecting and correcting medical errors in clinical notes using Large Language Models (LLMs)
Architecture of Apache Airflow, how DAGs help design complex flows and dependencies, and how we can leverage Apache airflow to train a ML Model and monitor.
Microsoft Learn Challenge conducting a challenge to get good in few of the challenges which are super useful to complete to gain knowledge on Microsoft Fabric.
Exploration and documentation of different services offered in GCP
Documenting the process of starting a company in india
A self-sufficient deep-dive on Azure Data Explorer (ADX/Kusto) — architecture, the KQL language from zero to advanced, ingestion patterns, performance/cost levers, and operational best practices.
Google and Kaggle provided good summary course on Gen AI , the blog contains details and highlights of the course.
Retrieval-Augmented Generation from first principles — embeddings, vector databases, chunking, retrieval, prompt construction, evaluation, and common failure modes — enough depth to build one yourself.
Using current speech augmented LLMs (SpeechLLMs) with realtime voice modality to understand user issues and to provide support and solutions.
Tool to convert an uploaded audio mixed with an image and generate a video format with image and uploaded audio in the video format.
A self-sufficient, production-minded walkthrough — from Docker internals to a hardened deploy on Azure App Service / Container Apps.
Leveraging Azure Data Factory for Scalable and Efficient Machine Learning Workflows
Initial version 1 of Astro app hosted at astroyuga.com
Changing the UI layout and improving the experience by modernizing the UI with custom styling
Accelerating Development and Deployment Cycles with AI Tools