Implement Transformers (and Deep Learning) from scratch in NumPy
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Updated
Oct 3, 2023 - Python
Implement Transformers (and Deep Learning) from scratch in NumPy
A deep exploration of loyalty as a multi-dimensional behavioral system shaped by intent, habit, and sensitivity. This article introduces a geometric framework for modeling customer behavior, predicting churn trajectories, and designing ML systems that understand loyalty as a dynamic state, not a metric.
A tiny deep neural network framework developed from scratch in C++ and CUDA.
A template for every machine learning project
Production-grade ML inference and training framework in pure Go. 234 tok/s on Gemma 3 1B — 18.8% faster than Ollama. Zero CGo, embeddable as a library, GGUF models, OpenAI-compatible API.
ML Pipeline Automation Tool - Chain together data processing, model training, and deployment with minimal code. Build production-ready ML workflows in minutes, not hours.
Deep Classiflie is a framework for developing ML models that bolster fact-checking efficiency. As a POC, the initial alpha release of Deep Classiflie generates/analyzes a model that continuously classifies a single individual's statements (Donald Trump) using a single ground truth labeling source (The Washington Post). For statements the model d…
An Agent-Computer Interface (ACI) for AI-driven machine learning.
Simple machine learning framework for Timeseries application to identify anomaly in dataset using Machine learning and Deep neural network
🤖 Solve ARC-AGI challenges efficiently using LLM-powered agentic AI for high accuracy and robust task performance.
Machine Learning 101
A machine learning framework with easy-to-use functions from Pytorch in Python.
Deep_classiflie_db is the backend data system for managing Deep Classiflie metadata, analyzing Deep Classiflie intermediate datasets and orchestrating Deep Classiflie model training pipelines. Deep_classiflie_db includes data scraping modules for the initial model data sources. Deep Classiflie depends upon deep_classiflie_db for much of its anal…
Official Repo of OpenArchX Framework.
Official Repo of OpenArchX Framework.
A Pythonic approach to object detection using Detectron2, a clean, modular framework for training and deploying computer vision models. DetectX simplifies the complexity of object detection while maintaining high performance and extensibility.
Personal ML Journey
Advanced regression analysis suite featuring KNN optimization, multi-algorithm comparison, hyperparameter tuning with Optuna, and production-ready ML pipelines with comprehensive model evaluation and visualization.
Python bindings for KortexDL - High-performance C++20 neural network framework with Intel MKL acceleration. Easy-to-use Python API with NumPy compatibility.
Unified AI/ML models repository with support for Gemini, OpenAI, Claude, DeepSeek, HuggingFace, and more. Production-ready implementations with streaming, async support, and comprehensive testing.
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