Popular GitHub Repositories for Keras Visualization

Build and share delightful machine learning apps, all in Python. ? Star to support our work!

Visualizer for neural network, deep learning and machine learning models

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

ncnn is a high-performance neural network inference framework optimized for the mobile platform

? A ranked list of awesome machine learning Python libraries. Updated weekly.

Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.

? Chat with your SQL database ?. Accurate Text-to-SQL Generation via LLMs using RAG ?.

Open standard for machine learning interoperability

Turns Data and AI algorithms into production-ready web applications in no time.

A neural network that transforms a design mock-up into a static website.

Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

Creative Coding: Generative Art, Data visualization, Interaction Design, Resources.

人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域

一款入门级的人脸、视频、文字检测以及识别的项目.

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Refine high-quality datasets and visual AI models

Techniques for deep learning with satellite & aerial imagery