This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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Technical resources for AI developers to build applications, agents, and systems using Oracle AI Database and OCI services
- artificial-intelligence
- generative-ai
- kubernetes
- kustomize
标注自己的数据集，训练、评估、测试、部署自己的人工智能算法
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
- machine-learning
- deep-learning
- lstm
- human-activity-recognition
小型金融知识图谱构建流程（neo4j / python / cypher / KG）
- cypher
- data-analysis
- graph-database
- neo4j
Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.
An interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at https://d2l.ai/.
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER
Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.
- milvus
- unstructured-data
- image-search
- audio-search
Jupyter notebook and datasets from the pandas video series
- data-science
- jupyter-notebook
- python
- pandas
CatBoost tutorials repository
- catboost
- tutorials
- ipython-notebook
- ipython
ZeroCostDL4Mic: A Google Colab based no-cost toolbox to explore Deep-Learning in Microscopy