Awesome GitHub RepositoriesTabular Data Preprocessing

This project is a collection of supervised and unsupervised machine learning algorithms implemented from scratch using Python. It serves as an educational resource for studying model training, parameter optimization, and the implementation of core predictive models. The library provides a variety of supervised learning tools, including linear and logistic regression, decision trees, and support vector machines. It also features unsupervised learning capabilities for discovering patterns in unlabeled datasets through clustering algorithms. Broad capability areas include ensemble learning thro

This project is a structured learning curriculum and technical reference for mastering deep learning with TensorFlow. It provides a comprehensive guide for building, training, and deploying neural networks, combining theoretical fundamentals with practical implementation examples. The repository distinguishes itself by covering the end-to-end machine learning workflow, from low-level tensor mathematics and linear algebra to the creation of complex model architectures. It includes specific guidance on developing data pipelines for diverse data types, such as images, text, and time-series seque

cuml هي مكتبة وإطار عمل للتعلم الآلي مسرع بواسطة GPU يستخدم CUDA لتسريع معالجة البيانات الجدولية وتنفيذ النماذج. توفر مجموعة من الأدوات لتدريب ونشر نماذج التصنيف، والانحدار، والتجميع على وحدات معالجة الرسومات NVIDIA وعناقيد GPU. تم تصميم المكتبة لقابلية التوسع، حيث توفر بيئة تعلم آلي موزعة على GPU يمكنها توزيع الحساب والبيانات عبر مسرعات أجهزة وعقد متعددة للتعامل مع مجموعات البيانات التي تتجاوز ذاكرة الجهاز الواحد. تعكس واجهات المقدر القياسية للسماح باستبدال النماذج القائمة على CPU بإصدارات مسرعة بواسطة GPU داخل سير العمل الحالي. يغطي المشروع مجموعة واسعة من قدرات التعلم الآلي، بما في ذلك التعلم الخاضع للإشراف، والتجميع غير الخاضع للإشراف، والبحث عن أقرب جار، وتقليل الأبعاد عالي الأبعاد. كما يتضمن معالجة بيانات جدولية مسرعة بواسطة الأجهزة لتوسيع الميزات والترميز، واستخراج ميزات النص، وتحليل السلاسل الزمنية، وقابلية تفسير تنبؤ النموذج. تشمل الأدوات المساعدة أدوات لإنشاء مجموعات بيانات اصطناعية، وتسلسل حالة النموذج، وحساب مقاييس أداء النموذج.

This repository is a comprehensive educational program and deep learning framework designed to teach practical deep learning using PyTorch through notebooks and code examples. It serves as a high-level library for building, training, and deploying neural networks, acting as a model training orchestrator that coordinates PyTorch models, optimizers, and loss functions. The project provides specialized toolkits for computer vision, natural language processing, and tabular data preprocessing. It distinguishes itself through advanced training controls such as discriminative learning rates, a two-w

This is a structured deep learning curriculum for programmers, delivered as a collection of Jupyter notebooks. It teaches the fundamentals of training neural networks for computer vision, natural language processing, tabular data analysis, and collaborative filtering using PyTorch and the fastai library. The course is designed to be hands-on, guiding learners from building a training loop from scratch to fine-tuning pretrained models for a variety of practical tasks. The curriculum distinguishes itself by covering the full lifecycle of a deep learning project, from data preparation and augmen

DataFrame is a C++ tabular data library and manipulation engine designed for managing heterogeneous data in contiguous memory. It functions as a statistical analysis framework and time series analysis toolkit, providing the means to store, index, and transform multidimensional datasets. The project distinguishes itself through a high-performance execution model that utilizes column-major storage, SIMD-aligned memory allocation, and a thread-pool for parallel computations. It employs a visitor-based algorithm dispatch system and policy-driven transformations to decouple data processing logic f