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MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 1mo ago

Sakana AI’s Error Diffusion Trains Dale-Compliant Dual-Stream Networks, Reaching 96.7% MNIST and 61.7% CIFAR-10 Without Backpropagation

Backpropagation relies on weight transport, which biological circuits likely cannot implement. Sakana AI's Error Diffusion sidesteps that constraint, training d

MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 1mo ago

Zyphra Releases ZUNA1.1: An Apache 2.0 EEG Foundation Model With Variable-Length Inputs From 0.5 To 30 Seconds

Zyphra released ZUNA1.1 on July 16, 2026, under the Apache 2.0 license. The 380M masked diffusion autoencoder reconstructs, denoises, and upsamples scalp-EEG ac

Netflix AI Team Cuts Wide-Partition Read Latency from Seconds to Milliseconds by Splitting Cassandra Partitions Per ID

MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 2mo ago

Netflix AI Team Cuts Wide-Partition Read Latency from Seconds to Milliseconds by Splitting Cassandra Partitions Per ID

Netflix engineers detailed how they handle wide partitions in Apache Cassandra for the TimeSeries Abstraction. Two approaches work together: Time Slice re-parti

MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 2mo ago

Using Graphify and NetworkX to Map Python Codebase Structure with God Nodes, Communities, and Architecture Visualizations

In this tutorial, we build a fully offline Graphify pipeline that turns a multi-module Python application into a knowledge graph. We install Graphify, generate

How to Build a Forecasting Pipeline with TimeCopilot Using Foundation Models and Automated Anomaly Detection

MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 2mo ago

How to Build a Forecasting Pipeline with TimeCopilot Using Foundation Models and Automated Anomaly Detection

We build an end-to-end forecasting workflow with TimeCopilot on a panel of real airline passenger data and a synthetic seasonal series with injected anomalies.

MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 2mo ago

Meet Flash-KMeans: An IO-Aware, Exact K-Means That Runs Over 200× Faster Than FAISS on GPUs

Flash-KMeans is an open-source, IO-aware implementation of standard Lloyd's k-means in Triton GPU kernels. It does not change the math or approximate. FlashAssi

A Coding Implementation on Spatial Graph Neural Networks for Urban Function Inference Using city2graph, OSMnx, and PyTorch Geometric

MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 2mo ago

A Coding Implementation on Spatial Graph Neural Networks for Urban Function Inference Using city2graph, OSMnx, and PyTorch Geometric

We build an end-to-end spatial graph learning pipeline using city2graph. We collect urban POI and street network data from OpenStreetMap, with a synthetic fallb

MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 2mo ago

A Coding Implementation on MONAI for End-to-End 3D Spleen Segmentation Using UNet on Medical CT Volumes

In this tutorial, we build an end-to-end 3D medical image segmentation pipeline using MONAI to segment the spleen on the Medical Segmentation Decathlon Task09 d

Building a Code Dataset Pipeline from NVIDIA Nemotron-Pretraining-Code-v3 Metadata with Streaming, Pandas, and tiktoken

MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 3mo ago

Building a Code Dataset Pipeline from NVIDIA Nemotron-Pretraining-Code-v3 Metadata with Streaming, Pandas, and tiktoken

In this tutorial, we work with NVIDIA's Nemotron-Pretraining-Code-v3 dataset as a large-scale metadata index for code pretraining research. We stream the datase

MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 3mo ago

Step by Step Guide to Build and Compare FedAvg and FedProx Federated Learning on Non-IID CIFAR-10 with NVIDIA FLARE

In this tutorial, we build an advanced federated learning experiment with NVIDIA FLARE. We compare FedAvg and FedProx on a non-IID CIFAR-10 setup, where client

Stochastic Gradient Descent (SGD’s) Frequency Bias and How Adam Fixes It

MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 3mo ago

Stochastic Gradient Descent (SGD’s) Frequency Bias and How Adam Fixes It

Modern language models are trained on data with extremely uneven token distributions. A small number of words appear in almost every sentence, while many rare b

How to Build a Single-Cell RNA-seq Analysis Pipeline with Scanpy for PBMC Clustering, Annotation, and Trajectory Discovery

MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 4mo ago

How to Build a Single-Cell RNA-seq Analysis Pipeline with Scanpy for PBMC Clustering, Annotation, and Trajectory Discovery

In this tutorial, we perform an advanced single-cell RNA-seq analysis workflow using Scanpy on the PBMC-3k benchmark dataset. We start by loading the dataset, i

MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 4mo ago

A Coding Implementation to Build a Conditional Bayesian Hyperparameter Optimization Pipeline with Hyperopt, TPE, and Early Stopping

In this tutorial, we implement an advanced Bayesian hyperparameter optimization workflow using Hyperopt and the Tree-structured Parzen Estimator (TPE) algorithm

How Knowledge Distillation Compresses Ensemble Intelligence into a Single Deployable AI Model

MarkTechPost 📐 ML Fundamentals ⚡ AI Lesson 5mo ago

How Knowledge Distillation Compresses Ensemble Intelligence into a Single Deployable AI Model

Complex prediction problems often lead to ensembles because combining multiple models improves accuracy by reducing variance and capturing diverse patterns. How