maziello

maziello's Stars

• krisograbek/resources-AI-Engineers

  6215

• vanna-ai/vanna

  🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using RAG 🔄.

  Language:Python10.8k839

• christianversloot/machine-learning-articles

  🧠💬 Articles I wrote about machine learning, archived from MachineCurve.com.

  3.4k716

• Garve/towards_data_science

  Language:Jupyter Notebook2614

• keithrozario/Klayers

  Python Packages as AWS Lambda Layers

  Language:Python2.1k308

• cuevas1208/fingerprint_recognition

  An implementations of fingerprint recognition algorithm

  Language:Python15553

• cokelaer/bioservices

  Access to Biological Web Services from Python.

  Language:Python27860

• ShishirPatil/gorilla

  Gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls)

  Language:Python11.2k934

• meta-llama/llama

  Inference code for Llama models

  Language:Python55.5k9.5k

• Mendeley/mendeley-api-python-catalog-example

  This is a simple example of an application that consumes the Mendeley API, using the Python SDK.

  Language:Python226

• timnon/pyschedule

  pyschedule - resource scheduling in python

  Language:Jupyter Notebook29161

• remi2257/sudoku-solver

  Smart solution to solve sudoku in VR

  Language:Python598125

• huggingface/notebooks

  Notebooks using the Hugging Face libraries 🤗

  Language:Jupyter Notebook3.6k1.5k

• microsoft/semantic-kernel

  Integrate cutting-edge LLM technology quickly and easily into your apps

  Language:C#21.3k3.1k

• itamargol/openai

  LLMs Best Tricks

  Language:Python32822

• mljs/ml

  Machine learning tools in JavaScript

  Language:JavaScript2.5k209

• facebookresearch/segment-anything

  The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook46.7k5.5k

• aws/deep-learning-containers

  AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.

  Language:Python994454

• Sanster/IOPaint

  Image inpainting tool powered by SOTA AI Model. Remove any unwanted object, defect, people from your pictures or erase and replace(powered by stable diffusion) any thing on your pictures.

  Language:Python18.8k1.9k

• aws-samples/amazon-sagemaker-immersion-day

  Language:Jupyter Notebook266221

• qubvel/segmentation_models

  Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

  Language:Python4.7k1k

• DENG-MIT/CRNN

  Chemical Reaction Neural Network

  Language:Julia7117

• tlastowka/calculate_multipart_etag

  Given a file and a chunk size in megabytes, calculates what the Amazon S3 etag will be.

  Language:Python1712

• Future-House/paper-qa

  High accuracy RAG for answering questions from scientific documents with citations

  Language:Python5.3k510

• MouseLand/cellpose

  a generalist algorithm for cellular segmentation with human-in-the-loop capabilities

  Language:Jupyter Notebook1.3k378

• FreshAirTonight/af2complex

  Predicting direct protein-protein interactions with AlphaFold deep learning neural network models.

  Language:Python14719

• nonoesp/AWS-Training-Custom-TensorFlow-Model-SageMaker

  🧠 Sample notebook to train a custom TensorFlow model in AWS SageMaker.

  Language:Jupyter Notebook6

• bluewhale28/Multiple-Instance-Learning-MIL-with-Keras-using-clear-cell-renal-cell-carcinoma-dataset

  Language:Jupyter Notebook2

• nicknochnack/SegmentationAPI

  Language:Jupyter Notebook177

• stitchfix/d3-jupyter-tutorial

  Language:JavaScript19791