Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
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This repository is maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), AI security, vulnerability research, exploit development, reverse engineering, and more. 🔥 Also check: https://hackertraining.org
- hacking
- penetration-testing
- hacking-series
- cybersecurity
Translated✅ (Completed) Super comprehensive deep learning notes [Tudui PyTorch] [Li Mu Dive into Deep Learning] [Andrew Ng Deep Learning] [Dafei LLM Agent]
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: 🇺🇸 🇨🇳 🇯🇵 🇮🇹 🇰🇷 🇷🇺 🇧🇷 🇪🇸
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
- computer-vision
- deep-learning
- drug-discovery
- forecasting
From the basics to slightly more interesting applications of Tensorflow
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
- seq2seq
- tensorflow
- tensorflow-tutorials
- python
Big Data essentials: Hadoop, MapReduce, Spark. Explore tutorials and demos in Jupyter notebooks—most are self-contained and live, ready to run with a click.
Sample code for Core ML using ResNet50 provided by Apple and a custom model generated by coremltools.
- ios
- coreml
- coreml-framework
- swift
Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.