Keras Libraries

69 Components & Libraries

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Keras Libraries

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

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Get started with W&B in four steps: That's it! Navigate to the W&B App to view a dashboard of your first W&B Experiment. Use the W&B App to compare multiple experiments in a unified…

Deep learning with satellite & aerial imagery

Extracting roads is challenging due to the occlusions caused by other objects and the complex traffic environment In instance segmentation, each individual 'instance' of a segmented area is given a u…

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. Flexible integration for any Python script: Build …

Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

IPython Notebook(s) and other programming tools such as Torch/Lua/D lang in demonstrating deep learning functionality. Additional PyRo tutorials: IPython Notebook(s) demonstrating scikit-learn functi…

Open source hardware and software platform to build a small scale self driving car.

Donkeycar is minimalist and modular self driving library for Python. It is developed for hobbyists and students with a focus on allowing fast experimentation and easy community contributions. The don…

Distributed Tensorflow, Keras and PyTorch on Apache Spark/Flink & Ray

Then, define the BigDL model using Keras-style API:

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

This repository contains all the code, notebooks and examples used in this book. We will also be adding bonus content here from time to time. So keep watching this space! Master the essential skills …

[UNMAINTAINED] Automated machine learning for analytics & production

Automated machine learning for production and analytics auto_ml is designed for production. Here's an example that includes serializing and loading the trained model, then getting predictions on sing…

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

For example: Recommended versions:

MLBox is a powerful Automated Machine Learning python library.

MLBox has been developed and used by many active community members. Your help is very valuable to make it better for everyone.

My first Python repo with codes in Machine Learning, NLP and Deep Learning with Keras and Theano

Codes in NLP, Deep Learning, Reinforcement Learning and Artificial Intelligence I am a Data Scientist and I code in R, Python and Wolfram Mathematica. Here you will find some Machine Learning, Deep L…

🏖 Keras Implementation of Painting outside the box

Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost

You should already have pip, Python, and optionally XGBoost, LightGBM, and CatBoost installed on your system (see below). Run the following command to install AlphaPy: Pyfolio is automatically instal…

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

This book brings the fundamentals of Machine Learning to you, using tools and techniques used to solve real-world problems in Computer Vision, Natural Language Processing, and Time Series analysis. T…

Machine learning on FPGAs using HLS

A package for machine learning inference in FPGAs. We create firmware implementations of machine learning algorithms using high level synthesis language (HLS). We translate traditional open-source ma…

Otto makes machine learning an intuitive, natural language experience. 🏆 Facebook AI Hackathon winner ⭐️ #1 Trending on MadeWithML.com ⭐️ #4 Trending JavaScript Project on GitHub ⭐️ #15 Trending (All Languages) on GitHub

To demo some of Otto's core features, try out the following: And feel free to get creative! Come up with your own machine learning goals and see where Otto takes you. Below is a step-by-step breakdow…

Unofficial implementation of "Image Inpainting for Irregular Holes Using Partial Convolutions". Try at: www.fixmyphoto.ai

In the paper they use a technique based on occlusion/dis-occlusion between two consecutive frames in videos for creating random irregular masks - instead I've opted for simply creating a simple mask-…

This project contains examples which demonstrate how to deploy analytic models to mission-critical, scalable production environments leveraging Apache Kafka and its Streams API. Models are built with Python, H2O, TensorFlow, Keras, DeepLearning4 and other technologies.

Here is some material about this topic if you want to read and listen to the theory instead of just doing hands-on: Here some more demos: The code is developed and tested on Mac and Linux operating s…

NBA sports betting using machine learning

A machine learning AI used to predict the winners and under/overs of NBA games. Takes all team data from the 2007-08 season to current season, matched with odds of those games, using a neural network…

Code, exercises and tutorials of my personal blog ! 📝

The repository is organized the following way : For the moment, these cheat sheets are written manually. I'd like to create a visual content later that would both dive in the maths and illustrate cle…

Python library to easily log experiments and parallelize hyperparameter search for neural networks

Test tube is a python library to track and parallelize hyperparameter search for Deep Learning and ML experiments. It's framework agnostic and built on top of the python argparse API for ease of use.…

A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.

Change detection based on remote sensing (RS) data is an important method of detecting changes on the Earth’s surface and has a wide range of applications in urban planning, environmental monitoring,…

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

Automatically save and learn from Experiment results, leading to long-term, persistent optimization that remembers all your tests. HyperparameterHunter provides a wrapper for machine learning algorit…

Python script for illustrating Convolutional Neural Networks (CNN) using Keras-like model definitions

Python script for illustrating Convolutional Neural Networks (CNN). Inspired by the draw_convnet project [1]. python-pptx (if you want to save models as pptx) Keras (if you want to convert Keras sequ…

U-Net: Convolutional Networks for Biomedical Image Segmentation

深度学习/人工智能/机器学习资料汇总(Deep Learning/Artificial Intelligent/Machine Learning) 持续更新……

🔥 New：本期新增神经网络与深度学习、ArXiv论文及代码、深度学习速查表及笔试面试精选等内容

Understanding emotions from audio files using neural networks and multiple datasets.

This project presents a deep learning classifier able to predict the emotions of a human speaker encoded in an audio file. The classifier is trained using 2 different datasets, RAVDESS and TESS, and …

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