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Latest from DeepHub IMBA

55 recent articles

DeepHub IMBA

Apr 6, 2026 · Artificial Intelligence

Mastering Machine Learning Feature Engineering: Scaling, Encoding, Aggregation, Embedding, and Automation

The article explains why good features matter more than fancy algorithms and walks through practical techniques—scaling, log transforms, binning, interaction, various encoding schemes, datetime extraction, text statistics, geospatial distances, aggregation, feature selection, and automated feature generation—illustrated with concrete pandas and scikit‑learn code examples.

automationencodingfeature engineering

0 likes · 16 min read

Mastering Machine Learning Feature Engineering: Scaling, Encoding, Aggregation, Embedding, and Automation

DeepHub IMBA

Apr 5, 2026 · Artificial Intelligence

Understanding ADK Multi‑Agent Orchestration: SequentialAgent, ParallelAgent, and LoopAgent Explained

The article explains ADK's three core orchestration modes—SequentialAgent for ordered pipelines, ParallelAgent for independent concurrent tasks, and LoopAgent for iterative quality‑control loops—detailing their suitable scenarios, state‑flow mechanisms, and how to build a complete order‑to‑delivery workflow without writing explicit orchestration code.

ADKLLMLoopAgent

0 likes · 16 min read

Understanding ADK Multi‑Agent Orchestration: SequentialAgent, ParallelAgent, and LoopAgent Explained

DeepHub IMBA

Apr 4, 2026 · Artificial Intelligence

Building Mini-vLLM from Scratch: KV‑Cache, Dynamic Batching, and Distributed Inference

This article walks through constructing Mini-vLLM, a from‑scratch LLM inference engine that tackles the O(N²) attention cost with KV‑cache, boosts throughput via dynamic batching, adds observability with Prometheus/Grafana, supports gRPC, and scales across multiple workers, with benchmark numbers demonstrating its CPU‑only performance.

DockerDynamic BatchingInference Engine

0 likes · 12 min read

Building Mini-vLLM from Scratch: KV‑Cache, Dynamic Batching, and Distributed Inference

DeepHub IMBA

Apr 3, 2026 · Artificial Intelligence

Multi‑Aspect Embedding: Integrating Context Signals into Vector Similarity Search

The article analyzes how traditional vector database pipelines use external filters for context constraints and proposes the Aspect Database’s multi‑aspect embedding approach, which encodes contextual attributes directly into similarity vectors to enable unified, context‑aware retrieval for AI systems.

AI systemsANN searchEmbedding

0 likes · 9 min read

Multi‑Aspect Embedding: Integrating Context Signals into Vector Similarity Search

DeepHub IMBA

Apr 2, 2026 · Artificial Intelligence

Speculative Decoding Explained: Small Draft Model + One‑Shot Verification

The article details how speculative decoding—using a fast small model to draft tokens and a large model to verify them—overcomes the memory‑bandwidth bottleneck of autoregressive inference, introduces SSD’s self‑draft and tree‑verification stages, presents real‑world benchmark gains, and shows how to enable it in vLLM.

GPU memory bandwidthSSDSpeculative Decoding

0 likes · 14 min read

Speculative Decoding Explained: Small Draft Model + One‑Shot Verification

DeepHub IMBA

Apr 1, 2026 · Fundamentals

10 Overlooked Pandas Vectorized Tricks That Boost Performance

The article presents ten built‑in Pandas vectorized operations—such as np.select, assign, cut/qcut, melt/pivot_table, describe, query, transform, to_datetime, explode, and string accessor methods—showing concise one‑liners, their verbose equivalents, and the typical speed gains they deliver on large DataFrames.

PerformancePythondata manipulation

0 likes · 12 min read

10 Overlooked Pandas Vectorized Tricks That Boost Performance

DeepHub IMBA

Mar 31, 2026 · Information Security

Can Prompt Injection Be Detected Without Storing Conversation Logs? A Privacy‑First Experiment

The article presents a privacy‑first system that extracts numeric telemetry from each LLM interaction, discards raw text, and evaluates whether detection of prompt injection and jailbreak attacks remains effective, showing only a 1.4 F1‑point drop when using solely text‑independent features.

LLM Securitybehavioral featuresjailbreak detection

0 likes · 9 min read

Can Prompt Injection Be Detected Without Storing Conversation Logs? A Privacy‑First Experiment

DeepHub IMBA

Mar 28, 2026 · Artificial Intelligence

Designing Core Multi‑Agent Systems: Task Decomposition and Dependency‑Graph Orchestration

The article analyzes how multi‑agent systems emulate human team dynamics through role specialization, structured handoffs, and cross‑validation, detailing the orchestration layer’s responsibilities—task decomposition, dependency‑graph scheduling, routing, and conflict resolution—while exposing common pitfalls, cost concerns, and framework choices.

LLM cost controlMulti-Agent SystemsState Management

0 likes · 19 min read

Designing Core Multi‑Agent Systems: Task Decomposition and Dependency‑Graph Orchestration

DeepHub IMBA

Mar 27, 2026 · Artificial Intelligence

AI Agent Architecture: Chain‑of‑Thought, ReAct, and Tool Calls

From a simple black‑box view where an agent receives a user request and returns an answer, the article breaks down modern AI agent designs—detailing the pure Chain‑of‑Thought reasoning loop, the ReAct reasoning‑acting cycle, tool integration, iteration tuning, and how to choose the optimal architecture for production.

AI agentsChain of ThoughtLLM architecture

0 likes · 9 min read

AI Agent Architecture: Chain‑of‑Thought, ReAct, and Tool Calls

DeepHub IMBA

Mar 26, 2026 · Artificial Intelligence

Information Access vs. Reasoning: Experimental Attribution Analysis of LLM Agent Performance

The study shows that LLM agents' apparent intelligence stems more from the amount and type of context they can access than from genuine reasoning ability, as demonstrated by the ContextEval framework’s controlled experiments across multiple hyper‑parameter optimization benchmarks.

AI evaluationLLM agentsagentic workflows

0 likes · 8 min read

Information Access vs. Reasoning: Experimental Attribution Analysis of LLM Agent Performance