1692 Open source projects that are alternatives of or similar to Test Tube

Deep Learning API and Server in C++14 support for Caffe, Caffe2, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE

A flexible framework of neural networks for deep learning

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Visualizer for neural network, deep learning, and machine learning models

Time Series Cross-Validation -- an extension for scikit-learn

[UNMAINTAINED] Automated machine learning for analytics & production

Deep Learning Computer Vision Algorithms for Real-World Use

A simple probabilistic programming language.

Notes for Deep Learning Specialization Courses led by Andrew Ng.

AI-related tutorials. Access any of them for free → https://towardsai.net/editorial

Applying Data Science and Machine Learning to Solve Real World Business Problems

deep-learning platforms,framework,data（深度学习平台、框架、资料）

AutoGluon: AutoML for Text, Image, and Tabular Data

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.

A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.

All the slides, accompanying code and exercises all stored in this repo. 🎈

Probabilistic reasoning and statistical analysis in TensorFlow

💫 Industrial-strength Natural Language Processing (NLP) in Python

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

TensorFlow implementation of the Value Iteration Networks (NIPS '16) paper

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

Practical Data Science with Ruby based tools.

Code for the AAAI 2018 publication "SEE: Towards Semi-Supervised End-to-End Scene Text Recognition"

A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. ONNX. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin, .onnx]

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks

ELKI Data Mining Toolkit

Code of the IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018 [read-only repository]

Neural network inference the Unix way

An open source python library for automated feature engineering

🤖 MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained

Distributed Deep Learning, with a focus on distributed training, using Keras and Apache Spark.

An intro to Python & programming for wanna-be data scientists

Build Graph Nets in Tensorflow

This is a collection of all the code that can be found on my YouTube channel Sigma Coding.

Run Keras models in the browser, with GPU support using WebGL

VIP cheatsheets for Stanford's CS 230 Deep Learning

The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)

another book on data science

Features selector based on the self selected-algorithm, loss function and validation method

A list of Twitter datasets and related resources.

A django website used in the book Practical Recommender Systems to illustrate how recommender algorithms can be implemented.

Ways of doing Data Science Engineering and Machine Learning in R and Python

ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

深度学习在推荐系统中的应用及论文小结。

📘 The interactive computing suite for you! ✨

Example project implementing best practices for PySpark ETL jobs and applications.

Statistical Machine Intelligence & Learning Engine

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

An open-source plotting library for statistical data.

Read data from, write data to, and modify the formatting of Google Sheets

Rumale is a machine learning library in Ruby

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

(Linear-chain) Conditional random field in PyTorch.

Easy pipelines for pandas DataFrames.

The 3rd edition of course.fast.ai

Enhance your application with the ability to see and interact with humans using any RGB camera.

Unix, R and python tools for genomics and data science